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Ketamine Metabolite (2R,6R)-Hydroxynorketamine Interacts with μ and κ Opioid Receptors
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  • Thomas T. Joseph*
    Thomas T. Joseph
    Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
    *Phone: +1 917 512 1664. Fax: +1 215 349 5078. Email: [email protected]
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    Orcidhttp://orcid.org/0000-0003-1323-3244
  • Weiming Bu
    Weiming Bu
    Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
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  • Wenzhen Lin
    Wenzhen Lin
    Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
    Department of Biochemistry and Molecular Biology, Guangxi Medical University, Nanning, Guangxi 530021, China
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  • Lioudmila Zoubak
    Lioudmila Zoubak
    National Institute of Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland 20852, United States
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  • Alexei Yeliseev
    Alexei Yeliseev
    National Institute of Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland 20852, United States
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  • Renyu Liu
    Renyu Liu
    Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
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  • Roderic G. Eckenhoff
    Roderic G. Eckenhoff
    Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
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  • Grace Brannigan
    Grace Brannigan
    Center for Computational and Integrative Biology and Department of Physics, Rutgers University, Camden, New Jersey 08102, United States
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    Orcidhttp://orcid.org/0000-0001-8949-2694
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ACS Chemical Neuroscience

Cite this: ACS Chem. Neurosci. 2021, 12, 9, 1487–1497
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https://doi.org/10.1021/acschemneuro.0c00741
Published April 27, 2021

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Abstract

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Ketamine is an anesthetic, analgesic, and antidepressant whose secondary metabolite (2R,6R)-hydroxynorketamine (HNK) has N-methyl-d-aspartate-receptor-independent antidepressant activity in a rodent model. In humans, naltrexone attenuates its antidepressant effect, consistent with opioid pathway involvement. No detailed biophysical description is available of opioid receptor binding of ketamine or its metabolites. Using molecular dynamics simulations with free energy perturbation, we characterize the binding site and affinities of ketamine and metabolites in μ and κ opioid receptors, finding a profound effect of the protonation state. G-protein recruitment assays show that HNK is an inverse agonist, attenuated by naltrexone, in these receptors with IC50 values congruous with our simulations. Overall, our findings are consistent with opioid pathway involvement in ketamine function.

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Introduction

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Part of the World Health Organization Model List of Essential Medicines, ketamine is administered primarily for its sedative and analgesic properties. One of its primary advantages in clinical medicine is hemodynamic stability compared to other common anesthetics such as propofol. It is also a rapidly acting antidepressant with striking efficacy particularly in severely depressed patients. In humans, pretreatment with naltrexone attenuates this antidepressant effect, suggesting the involvement of the opioid system. (1) Opioid antagonists also attenuate the antidepressant effect in a rodent model. (2)
Ketamine is described as an N-methyl-d-aspartate (NMDA) receptor antagonist, binds pentameric ligand-gated ion channels, (3,4) and binds and/or causes activation of various G-protein coupled receptors (GPCRs) including opioid and olfactory receptors. (5−10) A functional role for opioid receptor binding is suggested by inhibition of ketamine’s effect on the mouse tail flick test by opioid antagonists. (11) Further mouse studies showed that a greater antidepressant effect of R-ketamine than S-ketamine (12) and the metabolite (2R,6R)-hydroxynorketamine (HNK) demonstrated antidepressant activity. The mGlu2 receptor and brain-derived neurotrophic factor are thought to underlie this effect, (13,14) but a definitive molecular mechanism is not yet fully described.
Antidepressant effects might occur directly, through the binding of ketamine or its metabolites to GPCRs themselves, or indirectly, through modulation of endogenous opioid pathways. To evaluate the possibility of direct action on opioid receptors, using molecular dynamics (MD) simulations, we computationally characterized the binding of ketamine and its metabolites to μ and κ opioid receptors (MOR and KOR, respectively), determining both binding modes and affinities. Given the near-physiologic pKa of ketamine, protonation states of both the ligand and receptor were evaluated. We related these data to the results of G-protein recruitment assays. While neither ketamine nor norketamine had a significant effect on G-protein recruitment, HNK was an inverse agonist in both MOR and KOR, which is attenuated by naltrexone pretreatment. Consistent with and building upon previous work, (1,6,7,13) our findings describe a biophysical underpinning for the opioid-receptor-dependent antidepressant sequelae of ketamine.

Results and Discussion

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Ketamine Binds to Horse Spleen Apoferritin

As a validation of our methodology in a well-characterized protein, we first studied the interaction of S-ketamine with horse spleen apoferritin (HSAF). This 24-mer binds a variety of psychoactive molecules, such as propofol, isoflurane, sevoflurane, barbiturates, and the fluorescent general anesthetic 1-aminoanthracene (1-AMA), at an interfacial site between monomers similar to transmembrane binding sites in the GABAA receptor. (15−19)
In equilibrium MD simulations, both neutral and charged S-ketamine molecules placed in the interfacial binding site settled into a stable configuration in the site within 20 ns. Using free energy perturbation (FEP) MD, we calculated the binding affinities of these species. (17) Including solvation, restraint, and charge correction energies, the dissociation constant KD calculated by FEP MD of neutral S-ketamine was 562 nM, and that of protonated S-ketamine was >1 M. Because the interfacial binding site is relatively hydrophobic, it was unsurprising that the positively charged species of S-ketamine had such low affinity. Residues within 5 Å of the neutral S-ketamine, at least 50% of the time, were L24, S27, Y28, L31, A55, and R59.
We determined the corresponding experimental binding affinity of S-ketamine by measuring the fluorescence change upon its displacement of 1-AMA. At pH 7.0, KD was 42 μM (95% CI = 22.4 to 78.8 μM, Hill slope = −0.8 ± 0.25; Supporting Figure 1).
As ligand charge states exist in equilibrium, in order to compare the computational predictions with experimental results, we determined the contribution of each charge state to the overall binding affinity. In the aqueous state at pH = 7.0, the proportion of protonated ketamine is 76%, because its pKa = 7.5. (20) However, because in the bound state the effective pKa of functional groups can be shifted, (21) we did not know a priori what proportion of bound ligands was protonated. We derived this from the binding affinity of each ligand species (eqs 4 and 5; full derivation of the method in the Supporting Information). Because the protonated form has a much lower affinity, the experimental KD of 42 μM must primarily reflect the neutral form. The fraction of protonated S-ketamine is 98.7%, calculated using eq 4 as well as the simplified eq 5. In this case, the ligand pKa would effectively be 8.87 in the bound state. These calculations for all ligands and receptors evaluated in this manuscript are shown in Supporting Table 3.

Predicted Opioid Receptor Binding Conformations of Ketamine and Metabolites

We used MD simulations to predict the conformations of bound ketamine as well as its metabolites norketamine and (2R,6R)-hydroxynorketamine (HNK) in MOR and KOR. We evaluated both neutral and +1 charged H6.52 in each receptor, as we anticipated that this positively charged residue in the binding pocket would affect the ligand affinity. There were therefore eight conditions for ketamine, eight for norketamine, and four for HNK (because we did not vary its enantiomeric state), for a total of 20 simulations.
As with HSAF, we placed a ligand molecule in the orthosteric binding pocket of each free receptor and refined each pose using equilibrium MD. We chose this binding pocket because it is well-described in crystal structures and includes residues that interact with opioid ligands (D3.32, Y3.33, M3.36, and H6.52), and alternative sites are not well-described. Docking of each ligand in the binding pocket revealed a large variety of possible binding modes with similar scores (see Supporting Figure 2), which suggested that a docked conformation would not provide a reliable starting point for simulation. We evaluated R and S enantiomers of ketamine and norketamine and varied the protonation state of all ligands (0 or +1 charge), as well as the protonation state of H6.52 in the binding pocket (H297 in MOR and H291 in KOR).
Each ligand arrived at a resting bound configuration within 30 ns (Figure 1b, Supporting Figure 3). This was expected given the relatively few internal degrees of freedom of these compact molecules. Supporting Table 2 lists residues within 6.5 Å of each ligand in 50% or more of trajectory frames; these are largely orthosteric binding pocket residues. Only protonated ligands are listed, because they had much higher binding affinities (described below).

Figure 1

Figure 1. (a) Key residue interactions of protonated HNK in MOR and KOR. In each case, the ligand is in the orthosteric binding pocket. Note the presence of D3.32 (with hydrogen bond) and H6.52. See Supporting Table 2 for comprehensive list of nearby residues. (b) Root mean square deviation (RMSD) of ligand over simulation time in equilibrium MD simulations prior to FEP, for HNK. Plots for all ligands as well as receptor pocket available in the Supporting Information. (c) ΔG vs lambda plots of ligand–protein decoupling FEP simulations for HNK, both neutral (left) and protonated (right), illustrating the smoothness of these curves, which are representative of all FEP simulations. Calculations for MOR and KOR as well as both binding pocket His protonation states are shown. Forward and backward legs of these interleaved double-wide sampled simulations are shown. More detailed plots, where each curve is labeled, are available in the Supporting Information.

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Both enantiomers of ketamine interacted with similar subsets of residues in both MOR and KOR. In MOR, these included key interactions with D1473.32, Y1483.33, M1513.36, and H2976.52. D1473.32 and H2976.52 are key residues implicated in opioid binding. In KOR, both R- and S-ketamine interacted with D1383.32, Y1393.33, M1423.36, H2916.52, and W2876.48; the latter tryptophan is thought to interact with KOR agonists. (22)
R-Norketamine settled in the orthosteric binding pocket in MOR and KOR. MOR H297+ was the exception; the protonated R-norketamine settled into a separate binding pocket further from the lipid membrane, interacting primarily with transmembrane helices TM2 and TM7. In KOR, S-norketamine settled in a somewhat different orientation, interacting with L1012.46, A1042.49, D1052.50, and V1082.53 on TM2 but not D1383.32, Y1393.33, or H2916.52.
HNK bound the orthosteric binding pocket as well. Key interactions are included with D1473.32, Y1483.33, M1513.36, and H2976.52 in MOR and D1383.32, Y1393.33, M1423.36, and H2916.52 in KOR. In His+ receptors, HNK had more interactions with TM7 in both MOR and KOR (C7.38, A7.40, L7.41) than in the nonprotonated-His receptors.
The orthosteric binding pocket is water-exposed and can accommodate hydrophilic ligands (e.g., morphine at physiologic pH), though the vast majority of residues in the pocket are uncharged polar or hydrophobic; the charged residues are D2.50, D3.32, and H6.52. D3.32 interacted with the ligand in nearly all cases and would electrostatically stabilize a positive charge.

Predicted Binding Affinities of Ketamine and Metabolites to Opioid Receptors

Using double-decoupling FEP MD starting from the bound configurations determined above, we calculated the ligand binding affinity for each ligand–opioid receptor combination described above. This included decoupling charged species from the systems. Special attention was paid to mitigate the pitfalls of even state-of-the-art FEP MD for this difficult task. Electrostatic interactions of the charged ligand with charged residues in the binding pocket or with polar solvent have large interaction energy, and the final ΔG value will be the result of subtracting large numbers, so we used integrated double-wide sampling and multiple FEP runs to reduce this error. The interaction energy among charged periodic images resulting from decoupling of charged species causes overestimation of free energy change; we have used a standard box-size-dependent correction for this, described in the Methods section. Finally, for dynamics-based binding affinity calculations in general, protein conformational change upon binding may occur on too slow a time scale to be tractably sampled. Here, this would lead to systematic error in binding free energy predictions; to estimate convergence prior to FEP calculations, we quantified both ligand and binding pocket RMSD and bound-ligand rotational distributions (Supporting Figure 3).
We found, in general, that neutral ligands had low affinity (KD micromolar and above), but the protonated versions had high affinity (KD nanomolar and below) to both MOR and KOR (Figure 2 and Table 1). ΔG versus λ plots are shown in Figure 1 for HNK and in Supporting Figure 4 for all ligands. This result was reversed from the more hydrophobic binding site in HSAF and corresponded to the special case, discussed in the Methods section, of a rare but high-affinity ligand species.

Figure 2

Figure 2. Bar plots of binding affinities of ketamine and metabolites with opioid receptors. These figures include the cost of desolvation from aqueous solution and binding to the receptor.

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Table 1. Binding Free Energy (−ΔG) of Ketamine and Metabolites with GPCRs with Desolvation and Restraint Energies Includeda
 neutralprotonated
 –ΔG (kcal/mol)KD (μM)–ΔG (kcal/mol)KD (nM)
S-Ketamine
MORWT7.1 (6.5–7.9)7.9 (2.2–20)13.9 (12.6–15.2)0.096 (0.011–0.83)
 H297+7.6 (7.3–7.8)3.6 (2.4–5.3)10.5 (9.8–11.3)26 (7.5–89)
KORWT2.6 (2.6–2.6)13 000 (13 000–13 000)14.1 (13.5–14.6)0.072 (0.029–0.18)
 H291+4.9 (4.3–5.4)310 (130–740)8.4 (7.7–9.0)910 (310–2700)
R-Ketamine
MORWT7.8 (7.4–8.2)2.4 (1.3–4.5)12.0 (11.4–12.6)2.1 (0.75–5.6)
 H297+4.6 (3.3–5.8)490 (60–4000)10.8 (9.9–11.7)16 (3.6–72)
KORWT8.2 (7.9–8.6)1.1 (0.59–2.1)10.4 (9.2–11.5)32 (4.7–220)
 H291+2.9 (2.9–3.0)7500 (7100–8000)9.8 (9.1–10.5)88 (26–290)
S-Norketamine
MORWT2.7 (2.6–2.9)11 000 (8600–13 000)13.4 (12.3–14.5)0.22 (0.036–1.3)
 H297+3.8 (3.7–3.9)1900 (1600–2200)9.6 (8.6–10.6)120 (22–640)
KORWT5.2 (4.8–5.7)160 (84–320)9.5 (9.1–10.0)130 (62–270)
 H291+6.0 (5.7–6.2)49 (32–76)6.5 (6.1–6.8)21 000 (12 000–37 000)
R-Norketamine
MORWT8.3 (8.1–8.4)1.1 (0.84–1.5)16.4 (16.1–16.8)0.0014 (0.000 81–0.0024)
 H297+9.2 (9.1–9.3)0.22 (0.19–0.25)4.4 (3.3–5.5)690 000 (110 000–4 100 000)
KORWT2.0 (0.8–3.2)37 000 (5300–250 000)19.0 (18.8–19.2)0.000 020 (0.000 014–0.000 028)
 H291+4.9 (4.3–5.5)290 (110–740)16.5 (15.5–17.6)0.0012 (0.000 21–0.0062)
HNK
MORWT3.8 (1.9–5.7)1800 (75–45 000)11.4 (9.5–12.7)5.5 (0.71–140)
 H297+2.5 (1.7–3.2)16 000 (5300–64 000)8.3 (7.4–9.2)1000 (240–4600)
KORWT7.4 (7.3–7.5)4.5 (4.0–5.1)12.8 (11.7–13.9)0.57 (0.10–3.6)
 H291+1.5 (0.6–2.4)86 000 (20 000–370 000)15.6 (13.9–16.7)0.0052 (0.000 84–0.090)
a

KD values are calculated as described in Methods from respective ΔG values by FEP MD and correspond to K0 and K1 in equation 2 and . All energies are favorable for binding. Ranges represent minimum and maximum values obtained in both directions of FEP calculation, using interleaved double-wide sampling. WT = without protonation of orthosteric histidine; H291+ and H297+ refer to protonated (+1 charge) histidine (Ballesteros-Weinstein 6.52).

For all protonated ligands, binding affinity was decreased when the orthosteric binding pocket histidine had +1 charge adjacent to the ligand (MOR H2976.52+ and KOR H2916.52+), as would be expected from electrostatic repulsion. There was no clear pattern to the effect for neutral ligands. Overall, the magnitude of the change was much lower than that due to ligand charge.
The protonated S-ketamine had higher affinity to both MOR and KOR than protonated R-ketamine unless H6.52 had +1 charge. Protonated R-norketamine had greater affinity for KOR than protonated S-norketamine. Protonated HNK had greater affinity for KOR than MOR, but when this histidine was protonated in MOR, HNK affinity decreased; in KOR, it increased. This was attributable to migration of the positively charged HNK away from the protonated histidine in KOR, such that it was able to settle into a favorable configuration (see Supporting Table 1).
In certain cases (S- and R-norketamine, HNK in MOR and S-ketamine in KOR), with a +1 charge, H6.52 the ligand interacted more with TM2 (Supporting Table 2), so the calculated affinities for these systems are not directly comparable. The protonated R-norketamine had a lower binding affinity than neutral R-norketamine to MOR H297+ because of migration to its alternative binding site near TM2 and TM7. Of note, the negatively charged D2.50 is in TM2, which would stabilize a positively charged ligand. HNK had stronger affinity in KOR but weaker affinity in MOR as a result of the protonated histidine, possibly related to increased interactions with TM2.
Existing experimental proxies for ketamine binding affinity to opioid receptors are limited to Ki values from radioligand inhibition experiments. Representative Ki values for S- and R-ketamine, respectively, are 11 and 28 μM in MOR and 24 and 100 μM in KOR. (23) These are dependent on the hot ligand: (7,9,10,24) in this case, [3H]DAMGO for MOR and [3H]U69593 for KOR. If we make the nontrivial approximation that Ki can be substituted for KD, our calculated affinities were in several cases higher than mathematically possible to reconcile with these experimental values (Supporting Table 3). Of note, the ketamine radioligand inhibition experiments were done using brain homogenates or CHO cells. This suggests the possibility that ketamine, as a nonspecific binder, would bind other sites in the experimental preparation and be relatively unavailable for binding to opioid receptors, leading to experimental underestimation of the binding affinity relative to our theoretical estimates.

Signal Transducer Recruitment Assays of Ketamine

We measured G-protein recruitment by MOR and KOR as a function of ligand concentration using [35S]GTPγS assays (see Methods section). No clear effect due to ketamine was observed at clinically relevant concentrations. There was a suggestion of inverse agonism by both enantiomers of norketamine, but this was unclear (Supporting Figure 5). R-Ketamine appeared to induce G-protein recruitment in MOR starting at roughly 10 μM ligand concentration. S-Ketamine appeared to induce G-protein recruitment starting at roughly 25 μM concentration, although we could not determine EC50 values; this is because plateau activation would have required well in excess of physiologically reasonable concentrations.
We tested whether ketamine may be a neutral antagonist for the G-protein pathway. In MOR, adding progressively increasing concentrations of R-ketamine to MOR pretreated with 60 or 200 nM methadone, a known MOR agonist, showed inhibition of G-protein recruitment at high micromolar concentrations. We did not increase the ketamine concentration enough to determine IC50, as these would be physiologically irrelevant concentrations. In KOR, R-ketamine trended toward inhibition of G-protein recruitment induced by either 50 or 250 nM nalbuphine, a known KOR agonist, again only at very high concentrations (Supporting Figure 6).
Given the predicted affinities and minimal activity in these assays, we would have expected to observe competitive neutral antagonism by ketamine at lower concentrations. We can again speculate that other binding partners for ketamine present in membrane preparations limited the ketamine available for competition. Also, opioid receptors may dimerize and distort the kinetics of competitive inhibition. Finally, there might be a high-affinity secondary bound configuration in the same orthosteric pocket, where ketamine binding does not displace methadone or nalbuphine. Some of us have predicted a similar situation with another small ligands in another class A GPCR, the α-2A adrenergic receptor. (25) We concluded that ketamine might act as a neutral antagonist with respect to G-protein recruitment activity in both MOR and KOR; this activity is physiologically unimportant, or the experiment is confounded by the above factors.
Separately, we quantified β-arrestin recruitment as a function of S-ketamine concentration, for both MOR and KOR (see the Methods section). No significant change in β-arrestin recruitment was observed at micromolar or lower concentrations (Supporting Figure 7). We concluded that S-ketamine is an insignificant contributor to β-arrestin recruitment activity in both MOR and KOR.
As with radioligand inhibition assays, it is possible that [35S]GTPγS and β-arrestin assays may underestimate G-protein recruitment activity. These were conducted with cell-free membrane preparations, where the opioid receptors in question were amplified, but other membrane components are present in minimal quantities. Because ketamine and metabolites are not highly specific binders, the high-affinity charged ligand species may have relatively low availability at the binding pocket, resulting in less activation than would be expected from their affinities.

Inverse Agonism of HNK in MOR and KOR

In [35S]GTPγS assays with increasing ligand concentrations, HNK was an inverse agonist in both MOR and KOR (Figure 3). Fitting to a sigmoidal dose–response curve with a standard Hill slope of −1.0, the IC50 value for MOR was 0.56 nM (95% CI 0.41 to 4.7 nM), and for KOR, the IC50 was 2.1 × 10–5 nM. The latter extremely low IC50 value did not allow for a precise determination of confidence interval given the chosen ligand dilutions. For both MOR and KOR, the greatest degree of inhibition of G-protein recruitment was reached at 10 nM HNK; increased HNK concentrations did not increase inhibition.

Figure 3

Figure 3. Sigmoidal dose–response inhibition curves from [35S]GTPγS assays, including standard deviations. Increasing concentrations of HNK depress activation in both MOR and KOR, suggesting an inverse agonist effect. This is attenuated by pretreatment with naltrexone in both MOR and KOR.

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Given clinical evidence that pretreatment with naltrexone attenuates the antidepressant effect of ketamine, (1) we hypothesized that naltrexone would attenuate HNK inverse agonism. In repeat [35S]GTPγS assays with naltrexone pretreatment (1 μM in MOR and 10 μM in KOR), the inverse agonist effect of HNK was obliterated in MOR, and in KOR, the IC50 was increased to 110 nM (Figure 3).
With the caveat that they reflect different biochemical processes, we could consider these IC50 values as rough proxies for HNK dissociation constants. The KD values calculated by FEP MD represented lower affinity than suggested by non-naltrexone IC50 values even for the high-affinity +1 charge HNK: KD values were 5.5 nM for MOR and 0.57 nM for KOR. This made the calculation of the proportion of protonated bound ligand mathematically impossible; the experimental value must be between the two FEP-calculated values. Despite this, the MOR KD and IC50 values are within an order of magnitude, and the KOR IC50 is low but imprecise in this range; therefore, it is a reasonable hypothesis that the experimental and theoretical values are compatible. Notably, FEP MD predicted a higher affinity of HNK to KOR than to MOR, which was borne out in the experiment.

Conclusions

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In this study, we revealed molecular details of the bound configurations of ketamine and its metabolites to opioid receptors. We showed that the metabolite HNK has a high calculated affinity in the orthosteric binding site and is an inverse agonist for G-protein recruitment in both MOR and KOR in vitro and that this effect is inhibited by naltrexone pretreatment. This provides biochemical context to previous evidence suggesting that ketamine’s antidepressant effect is attenuated by naltrexone pretreatment. The IC50 values for HNK–MOR/KOR inverse agonism are in the low-nanomolar range, consistent with the relatively low doses of ketamine used in humans for depression: An example regimen is 0.1–0.75 mg/kg administered in an infusion over 40 min. (26)
Our data are consistent with the hypothesis that HNK is the primary ketamine-related compound with antidepressant activity and implicate G-protein recruitment by MOR and/or KOR as part of the molecular mechanism. Ostensibly, HNK binding allosterically modulates the conformation of TM5-7, in turn affecting G-protein recruitment, as proposed in other class A GPCRs. (27−29) We speculate that these helices are stabilized, reducing constitutive G-protein recruitment and resulting in the inverse agonist effect. While ketamine and norketamine also have favorable binding affinities, we did not show that they have significant effects on G-protein recruitment.
This study cannot confirm whether HNK itself acts directly as an antidepressant or is part of a larger indirect mechanism involving the opioid system. There is controversy on this topic, with conflicting results in mouse models. (13,34−36) We speculate that mouse models may not capture the same pathology as that underlying human depression. We propose that interaction of HNK with opioid receptors partly underlies the antidepressant activity, complementing previously described mechanisms involving mGlu2 and BDNF.
We did not address potential structural contributors to G-protein recruitment that could differentiate the neutral activity of ketamine from the inverse agonism of HNK. The patterns of ligand–residue interactions that confers agonist, antagonist, or inverse agonist activity in opioid receptors are as yet not fully described, (32) though we envision future work attacking this problem for HNK. We do not consider here the possibilities of GPCR oligomerization or opioid receptor modulation indirectly by peptides. The mechanism of G-protein recruitment is an active area of investigation, with, for example, a recent description of the structure of an agonist bound KOR with Gi. (33) We cannot yet exclude β-arrestin-dependent activity in MOR and KOR from ligands other than S-ketamine. In addition, there is evidence in rodent models that S-norketamine has antidepressant activity, (30,31) which is intriguing given the suggestion of inverse agonism for this compound in the present study. Further investigation of norketamine could be considered.
Through the exploration of the relationship of affinity values with fractions of protonated ligand, we have provided a way to check how well experimental KD values reconcile with calculated affinities in this type of system. When the measured KD is correct and calculated affinities for each protonation state are both correct and reflect energetically plausible macrostates (e.g., the charge configuration of the binding pocket exists as simulated with ligand bound), a plausible distribution of ligand protonation states (and effective pKa) is yielded. This method gave a reasonable result in HSAF where we were able to measure KD.
Overall, our results support and build upon the finding by Williams et al. that implicates the opioid system in ketamine’s antidepressant activity by showing that pretreatment with naltrexone attenuates this effect. (1) More work is required in this area. There may be benefit to further study in cell-based systems to address these questions, particularly in more clearly defining the cellular-level consequences of inverse agonism by HNK. We expect that continued study of both the molecular interactions of HNK as well as its potential use as an antidepressant will benefit human health.

Methods

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We evaluated ketamine as well as its metabolites norketamine and (2R,6R)-hydroxynorketamine. We included R- and S-enantiomers for ketamine and norketamine and their protonated states.

Force Field Parameters

Molecular mechanics (MM) force field parameters for each ligand molecule, both neutral and charged versions, were required for MD simulations. No high-quality MM parameters with the CHARMM force field (37,38) were available. We initially used the ParamChem web server to choose parameters for each ligand using the CGenFF force field, (39,40) but this approach did not produce satisfactory parametrizations with sufficiently low ParamChem-reported penalty scores. Therefore, we manually refined those parameters. We employed QM methods, following the Force Field Took Kit workflow (41) with modifications, (42) including dihedral interaction corrections as necessary.
Quantum mechanics geometry optimizations and energy calculations were done with Gaussian09 Rev. E01 (Gaussian, Inc., Wallingford, CT, USA), at the B3LYP/6-31G** level of theory and basis set, for parity with parametrization approaches commonly used with the CHARMM force field. These were used to provide an initial minimized structure as well as “gold standard” energies with which the MM parameters could be fit.
Enthalpies of vaporization (sublimation) for each ligand were calculated as ΔHvap = ⟨Ugas⟩ – ⟨Ucondensed⟩/N + RT, where each U is the respective potential energy, angle brackets denote averages, N is the number of molecules, R is the gas constant, and T is the temperature. The potential energy averages were taken from simulations of a single ligand molecule in gas phase (2 ns) and of 300 ligand molecules in a periodic box (10 ns, NPT ensemble). Densities were calculated from the condensed phase simulations. We are unaware of experimental correlates of these parameters in the literature, but the heats of vaporization correlate with those calculated with the Joback method (43) and adjusted to the simulation temperature. Desolvation energies (i.e., from aqueous to gas phase) were calculated by FEP MD as the energy of decoupling a single ligand molecule from a box of TIP3P water using the protocol described below. All these values are listed in Supporting Table 1.

Experimental Determination of Ketamine–HSAF Binding Affinity

In order to relate our approach to a model experimental system, we determined the binding affinity of S-ketamine to horse spleen apoferritin (HSAF). Fluorescence competition assays were performed as previously reported. (19) The binding affinity of S-ketamine was determined by equilibrium binding of increasing amounts of S-ketamine with constant concentrations of 1-aminoanthracene (1-AMA) and HSAF. HSAF (0.3 μM) in 20 mM phosphate and 130 mM NaCl buffer at pH 7 was equilibrated with 11 μM 1-AMA. Each sample was made by adding a given concentration of S-ketamine (1 μM to 4 mM) in the same buffer to obtain 0.5 μL of total volume, mixing, and immediately measuring on a Shimadzu RF-5301PC spectrofluorophotometer (Shimadzu Corp., Kyoto, Japan). The fluorescence spectrum of 1-AMA was determined using light at 380 nm for excitation and recording emission at 510 nm. Excitation and emission slit widths were 5 and 10 nm, respectively. Fluorescence data were collected from 400 to 720 nm. All samples were run in triplicate. A fluorescence signal decrease from 1-AMA was observed as S-ketamine was titrated, indicating competition for binding. Data and error analysis were carried out using Prism 5.0 (GraphPad Software, La Jolla, CA, USA). Fluorescence was corrected by simple subtractions of baseline values for 1-AMA and HSAF. Fluorescence intensity versus concentration data were fit to variable slope Hill models. The Cheng-Prusoff equation was used to correct for the presence of the 1-AMA competitor.
S-Ketamine and (2R,6R)-hydroxynorketamine were obtained from Sigma-Aldrich (K1884, SML1873). R-Ketamine was obtained from Cayman Chemical (16519). The R- and S-norketamine were obtained from Tocris (5996, 6112).

G-Protein Activation ([35S]GTPγS) Assay

In this assay, levels of radioactive 35S-γ-GTP were measured after incorporation in the recruited G-protein complex. (44) MOR membrane preparation was obtained from EMD Millipore (cat. number HTS101M) and PerkinElmer (cat. number 611055840UA), and KOR membrane preparation was obtained from PerkinElmer (cat. number ES-542-M400UA). The ligand was incubated with this membrane preparation. A G-protein preparation containing Gα, Gβ, Gγ, and radiolabeled GTP were added so that recruitment could occur. This reaction was then quenched, and free radiolabeled GTP was washed away; the remaining amount of radioactive 35S-γ-GTP bound to a Gα subunit was measured by its radioactivity in a scintillation counter as described previously. (45) All experiments were run two to three times and, within each experiment, in duplicate at each data point. For each curve, one representative experiment is presented. Results in the form of scintillation counts were analyzed using GraphPad Prism 8.0 (GraphPad Software, San Diego, CA), and EC50/IC50 values were calculated by fit to a sigmoidal dose–response curve with a standard Hill slope of 1.0 or −1.0.

β-Arrestin Recruitment Assay

The previously described protocol was followed. (46) In brief, HTLA cells, an HEK293 cell line stably expressing a tTA-dependent luciferase reporter and a β-arrestin2-TEV fusion gene, were maintained in DMEM with 10% FBS, 2 μg/mL puromycin, and 100 μg/mL hygromycin B in a humidified atmosphere at 37 °C in 5% CO2. For the transfection, cells were plated to 50–80% confluency and transfected with OPRM1 (for MOR) or OPRK1 (for KOR) using FuGENE HD (Promega Corp., Madison, WI, USA). The next day, transfected cells were trypsinized and transferred into poly-l-lysine coated and rinsed 96-well, white, clear-bottom cell culture plates in 50 μL of DMEM containing 1% dialyzed FBS and 1X penicillin/streptomycin at a density of 20 000 cells/well. After 7 h, 6X drug solutions were prepared in assay buffer (1X HBSS with 20 mM HEPES, pH 7.4), and 10 μL was added to each well. The following day, 60 μL of Bright Glo (Promega Corp.), diluted 4-fold, was added to each well and incubated 5 min at room temperature in the dark before luminescence was measured. Results in the form of luminescence units were analyzed using GraphPad Prism.

Simulations

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We conducted equilibrium MD simulations of ligands bound to HSAF and μ and κ opioid receptors (MOR and KOR, respectively) derived from crystal structures (47−49) (Protein Data Bank: 3F32, 5C1M, 4DJH). Missing residues were modeled with MODELER ModLoop. (50) We used the inactive form of KOR available at the time of the study. The more recent nanobody-stabilized active form of KOR has a similar binding pocket, differing primarily in the displacement of TM6 and TM7 helices. (48)
We used CHARMM-GUI (51) to embed each protein in a 70:30 ratio 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine:cholesterol lipid bilayer, with surrounding TIP3P water, 0.15 M NaCl, and excess ions for electroneutrality. The crystallographic cholesterol in MOR was preserved. We used the CHARMM36 force field with our ligand parameters. A single ligand molecule was placed in each orthosteric binding site, consistent with the location of the orthosteric binding pocket in crystal structures as well as docking calculations with AutoDock Vina, (52) to provide the starting configuration for subsequent MD simulations. The docking calculations, using flexible side chains in the orthosteric pocket, yielded a wide variety of ligand configurations distributed throughout the pocket (see Supporting Figure 2). As side chain flexibility would be important to the resting configuration of these relatively small and simple ligands in a way that the simplified potential function of docking may not capture, we elected to use MD for refinement of the ligand coordinates. All simulations were conducted with NAMD 2.12 or 2.13 molecular dynamics software, (53) using GPUs where possible. Minimization and equilibration with solute restraints preceded production simulation in the NPT ensemble. Each ligand was simulated in the binding site for at least 30 ns in equilibrium production MD simulation.
In order to assess whether these simulations arrived at a resting bound configuration, we calculated the root-mean-square deviation (RMSD) of the ligands in the binding pockets (Supporting Figure 3a) by first fitting the receptor with respect to the backbone of the first production simulation frame to remove global rotation and translation and then calculating the RMSD of the ligand heavy atoms with respect to the first production simulation frame. The RMSD of the binding pocket atoms was similarly calculated (Supporting Figure 3b). The distribution of the rotation angles of the ligands in the pocket was calculated as well (Supporting Figure 3c).
Using FEP MD, we then calculated the standard binding affinity of each ligand to the receptor as the negative of the energy of dissociation from the receptor into bulk water. FEP MD has been successfully used for calculating accurate ligand affinities in the class A GPCR orthosteric pocket. (54−56) There were 30–50 windows per run for each leg, with 0.4 ns of equilibration plus 2 ns of production simulation per window and λ schedules modified for more sampling in regions with large-magnitude energy changes; each FEP run included a minimum of 62 ns of production simulation, for a total of ∼3.2 μs in FEP MD simulations including replicates. Interleaved double-wide sampling was used, with sampling in both forward and backward directions at each λ. To facilitate parallel execution, the FEP windows were separated into groups of five, each starting from the same configuration. The first window in each group used 1 ns rather than 0.4 ns of equilibration time. Multiple runs were conducted for some systems; all results were averaged. A flat-bottomed spherical volume restraint of radius 5 Å was applied to the ligand center-of-mass to reduce the sampling of very low probability states by the partly decoupled ligand. (55,57) The thermodynamic process was therefore as follows: decoupling from the receptor with the restraint, plus a correction for the restraint, plus the energy of recoupling the ligand to water. The free energy cost of imposing the restraint was calculated as , where V* is the volume of the sphere, V is the effective volume occupied by a single ligand at 1 M concentration (∼1660 Å3), R is the gas constant, and T is the temperature. For the 5 Å sphere this penalty was 0.69 kcal/mol.

Correction for Particle Mesh Ewald (PME) Summation across Nonzero-Charge Systems During FEP MD

The FEP MD calculations of charged ligands by definition included non-neutral intermediate states, which shifts the electrostatic potential baseline due to the use of periodic boundary conditions and Ewald summation, and the resulting error in the computed free energy change scales as the inverse of the box length. (58−60) This is a significant source of error, even in the setting of charged species having large-magnitude binding free energies when the binding pocket includes charged residues, as is the case in MOR and KOR. We calculated this relevant correction using the formula in Hummer et al. (60) as −2.837297/L, where L is the box length and the equation is expressed in atomic units. For protein simulations, which were noncubic, L was chosen as the length of a cube of the same volume as the simulation. These corrections were included in the ΔG and KD values reported.

Binding Model for Two Ligand Species

Because each binding affinity calculation applies to a single ligand (and protein) protonation state, we must separately determine the proportions of these states to determine their contribution to the overall binding affinity. By the same token, given both an experimental dissociation constant KD as well as a computational state-specific KD, we can predict the proportions of the protonation states. A brief description follows; the full derivation is available in the Supporting Information.
We take the probability of the occupancy of a protein binding site to be
(1)
where [L] is the concentration of the ligand (including all protonation states) and KD is the dissociation constant (note that when [L] = KD then P = 0.5). Including two protonation states, we define the occupancy of the site
(2)
where each fj is the proportion of systems in protonation state j, Kj is the ligand dissociation constant in protonation state j, and f0 + f1 = 1. The third term in eq 2 excludes the possibility of both ligands occupying the same site. Defining the fraction-weighted dissociation constants λ0 = K0/f0 and λ1 = K1/f1 yields
(3)
Let us call the dissociation constant across both protonation states K′D, such that when [L] = K′D, Peither = 1/2. Setting the left-hand side of eq 3 to 1/2 and solving for [L] yields
(4)
In the special case where the protonated form has an extremely low affinity, so λ1 ≫ λ0, then . Similarly, if the protonated form binds much more strongly than the neutral form, λ1 ≫ λ0 and . So, to solve for f1 in these special cases, we can use simplified expressions:
(5)
It is important to note that rare forms of the ligand may still determine the observed K′D if they have much higher affinities than those of the common form. In such a case, the dissociation constant observed from ligand titration would significantly overestimate the actual dissociation constant for the high-affinity species.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acschemneuro.0c00741.

  • Detailed derivation of the binding model for two ligand species, densities and enthalpies of vaporization/sublimation, residues, ligand pKa, fluorescence curves, docked conformations, RMSDs, free energy perturbation molecular dynamics energy plots, G-protein activation assays, Competition [35S]GTPgS assays, and β-arrestin recruitment assays (PDF)

Terms & Conditions

Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

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  • Corresponding Author
  • Authors
    • Weiming Bu - Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
    • Wenzhen Lin - Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States;  Department of Biochemistry and Molecular Biology, Guangxi Medical University, Nanning, Guangxi 530021, China
    • Lioudmila Zoubak - National Institute of Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland 20852, United States
    • Alexei Yeliseev - National Institute of Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland 20852, United States
    • Renyu Liu - Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
    • Roderic G. Eckenhoff - Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States
    • Grace Brannigan - Center for Computational and Integrative Biology and Department of Physics, Rutgers University, Camden, New Jersey 08102, United States;  Orcidhttp://orcid.org/0000-0001-8949-2694
  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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T.T.J. was supported by the National Institutes of Health postdoctoral training grant 5T32GM112596 and the Foundation for Anesthesia Education and Research (MRTG-BS-Joseph). High-performance computing resources and support were provided by the Office of Advanced Research Computing and RDI2 at Rutgers University and National Science Foundation XSEDE (award TG-MCB170017 to T.T.J.). R.L. was supported by 1R01GM111421, National Institutes of Health. A.Y. and L.Z. were supported by the intramural research program, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health.

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    The interaction of ketamine with the opiate receptor
    Smith, David J.; Pekoe, Gary M.; Martin, Louis L.; Coalgate, Barbara
    Life Sciences (1980), 26 (10), 789-95CODEN: LIFSAK; ISSN:0024-3205.
    The analgesic effect of the anesthetic agent (±)-ketamine-HCl (I-HCl) [1867-66-9] was inhibited in rats by the narcotic receptor antagonist naloxone. Racemic I-HCl also displaced naloxone-3H in an opiate receptor binding assay. The potency of I in the assay was reduced nearly 6-fold by Na+, suggesting that the drug interacts as an agonist. However, some activity as an antagonist was not ruled out. The interaction of I with the opiate receptor was stereospecific, with the (+)-salt [33795-24-3] being more effective than the (-)-salt [33643-47-9]. The stereoselective nature of the interaction is consistent with other studies demonstrating that (+)-I-HCl has a greater analgesic effect than the (-)-I salt.
  11. 11
    Pacheco, D. d. F., Romero, T. R. L., and Duarte, I. D. G. (2014) Central Antinociception Induced by Ketamine Is Mediated by Endogenous Opioids and μ- and δ-Opioid Receptors. Brain Res. 1562, 69– 75,  DOI: 10.1016/j.brainres.2014.03.026
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    11
    Central antinociception induced by ketamine is mediated by endogenous opioids and μ- and δ-opioid receptors
    Pacheco, Daniela da Fonseca; Romero, Thiago Roberto Lima; Duarte, Igor Dimitri Gama
    Brain Research (2014), 1562 (), 69-75CODEN: BRREAP; ISSN:0006-8993. (Elsevier B.V.)
    It is generally believed that NMDA receptor antagonism accounts for most of the anesthetic and analgesic effects of ketamine, however, it interacts at multiple sites in the central nervous system, including NMDA and non-NMDA glutamate receptors, nicotinic and muscarinic cholinergic receptors, and adrenergic and opioid receptors. Interestingly, it was shown that at supraspinal sites, ketamine interacts with the μ-opioid system and causes supraspinal antinociception. In this study, we investigated the involvement of endogenous opioids in ketamine-induced central antinociception. The nociceptive threshold for thermal stimulation was measured in Swiss mice using the tail-flick test. The drugs were administered via the intracerebroventricular route. Our results demonstrated that the opioid receptor antagonist naloxone, the μ-opioid receptor antagonist clocinnamox and the δ-opioid receptor antagonist naltrindole, but not the κ-opioid receptor antagonist nor-binaltorphimine, antagonized ketamine-induced central antinociception in a dose-dependent manner. Addnl., the administration of the aminopeptidase inhibitor bestatin significantly enhanced low-dose ketamine-induced central antinociception. These data provide evidence for the involvement of endogenous opioids and μ- and δ-opioid receptors in ketamine-induced central antinociception. In contrast, κ-opioid receptors not appear to be involved in this effect.
  12. 12
    Zhang, J., Li, S., and Hashimoto, K. (2014) R (−)-Ketamine Shows Greater Potency and Longer Lasting Antidepressant Effects than S (+)-Ketamine. Pharmacol., Biochem. Behav. 116, 137– 141,  DOI: 10.1016/j.pbb.2013.11.033
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    R (-)-ketamine shows greater potency and longer lasting antidepressant effects than S (+)-ketamine
    Zhang, Ji-chun; Li, Su-xia; Hashimoto, Kenji
    Pharmacology, Biochemistry and Behavior (2014), 116 (), 137-141CODEN: PBBHAU; ISSN:0091-3057. (Elsevier)
    The N-methyl-D-aspartate (NMDA) receptor antagonist ketamine is one of the most attractive antidepressants for treatment-resistant major depressive disorder (MDD). Ketamine (or RS (±)-ketamine) is a racemic mixt. contg. equal parts of R (-)-ketamine and S (+)-ketamine. In this study, we examd. the effects of R- and S-ketamine on depression-like behavior in juvenile mice after neonatal dexamethasone (DEX) exposure. In the tail suspension test (TST) and forced swimming test (FST), both isomers of ketamine significantly attenuated the increase in immobility time, seen in DEX-treated juvenile mice at 27 and 29 h resp., after ketamine injections. In the 1% sucrose preference test (SPT), both isomers significantly attenuated the reduced preference for 1% sucrose consumption in DEX-treated juvenile mice, 48 h after a ketamine injection. Interestingly, when immobility times were tested by the TST and FST at day 7, R-ketamine, but not S-ketamine, significantly lowered the increases in immobility seen in DEX-treated juvenile mice. This study shows that a single dose of R-ketamine produced rapid and long-lasting antidepressant effects in juvenile mice exposed neonatally to DEX. Therefore, R-ketamine appears to be a potent and safe antidepressant relative to S-ketamine, since R-ketamine may be free of psychotomimetic side effects.
  13. 13
    Zanos, P., Highland, J. N., Stewart, B. W., Georgiou, P., Jenne, C. E., Lovett, J., Morris, P. J., Thomas, C. J., Moaddel, R., Zarate, C. A., and Gould, T. D. (2019) (2R,6R)-Hydroxynorketamine Exerts MGlu2 Receptor-Dependent Antidepressant Actions. Proc. Natl. Acad. Sci. U. S. A. 116 (13), 6441– 6450,  DOI: 10.1073/pnas.1819540116
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    13
    (2R,6R)-hydroxynorketamine exerts mGlu2 receptor-dependent antidepressant actions
    Zanos, Panos; Highland, Jaclyn N.; Stewart, Brent W.; Georgiou, Polymnia; Jenne, Carleigh E.; Lovett, Jacqueline; Morris, Patrick J.; Thomas, Craig J.; Moaddel, Ruin; Zarate, Carlos A. Jr.; Gould, Todd D.
    Proceedings of the National Academy of Sciences of the United States of America (2019), 116 (13), 6441-6450CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    Currently approved antidepressant drugs often take months to take full effect, and a$$Hat$$ 1/430% of depressed patients remain treatment resistant. In contrast, ketamine, when administered as a single subanesthetic dose, exerts rapid and sustained antidepressant actions. Preclin. studies indicate that the ketamine metabolite (2R,6R)-hydroxynorketamine [(2R,6R)-HNK] is a rapid-acting antidepressant drug candidate with limited dissocn. properties and abuse potential. We assessed the role of group II metabotropic glutamate receptor subtypes 2 (mGlu2) and 3 (mGlu3) in the antidepressant-relevant actions of (2R,6R)-HNK using behavioral, genetic, and pharmacol. approaches as well as cortical quant. EEG (qEEG) measurements in mice. Both ketamine and (2R,6R)-HNK prevented mGlu2/3 receptor agonist (LY379268)-induced body temp. increases in mice lacking the Grm3, but not Grm2, gene. This action was not replicated by NMDA receptor antagonists or a chem. variant of ketamine that limits metab. to (2R,6R)-HNK. The antidepressant-relevant behavioral effects and 30- to 80-Hz qEEG oscillation (gamma-range) increases resultant from (2R,6R)-HNK administration were prevented by pretreatment with an mGlu2/3 receptor agonist and absent in mice lacking the Grm2, but not Grm3a$$Hat$$ /a$$Hat$$ , gene. Combined subeffective doses of the mGlu2/3 receptor antagonist LY341495 and (2R,6R)-HNK exerted synergistic increases on gamma oscillations and antidepressant-relevant behavioral actions. These findings highlight that (2R,6R)-HNK exerts antidepressant-relevant actions via a mechanism converging with mGlu2 receptor signaling and suggest enhanced cortical gamma oscillations as a marker of target engagement relevant to antidepressant efficacy. Moreover, these results support the use of (2R,6R)-HNK and inhibitors of mGlu2 receptor function in clin. trials for treatment-resistant depression either alone or in combination.
  14. 14
    Fukumoto, K., Fogaça, M. V., Liu, R.-J., Duman, C., Kato, T., Li, X.-Y., and Duman, R. S. (2019) Activity-Dependent Brain-Derived Neurotrophic Factor Signaling Is Required for the Antidepressant Actions of (2R,6R)-Hydroxynorketamine. Proc. Natl. Acad. Sci. U. S. A. 116 (1), 297– 302,  DOI: 10.1073/pnas.1814709116
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    14
    Activity-dependent brain-derived neurotrophic factor signaling is required for the antidepressant actions of (2R,6R)-hydroxynorketamine
    Fukumoto, Kenichi; Fogaca, Manoela V.; Liu, Rong-Jian; Duman, Catharine; Kato, Taro; Li, Xiao-Yuan; Duman, Ronald S.
    Proceedings of the National Academy of Sciences of the United States of America (2019), 116 (1), 297-302CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    Ketamine, a noncompetitive N-methyl-d-aspartate (NMDA) receptor antagonist, produces rapid and long-lasting antidepressant effects in major depressive disorder (MDD) patients. (2R,6R)-Hydroxynorketamine [(2R,6R)-HNK], a metabolite of ketamine, is reported to produce rapid antidepressant effects in rodent models without the side effects of ketamine. Importantly, (2R,6R)-HNK does not block NMDA receptors like ketamine, and the mol. signaling mechanisms for (2R,6R)-HNK remain unknown. Here, we examd. the involvement of BDNF/TrkB/mechanistic target of rapamycin complex 1 (mTORC1) signaling in the antidepressant actions of (2R,6R)-HNK. Intramedial prefrontal cortex (intra-mPFC) infusion or systemic (2R,6R)-HNK administration induces rapid and long-lasting antidepressant effects in behavioral tests, identifying the mPFC as a key region for the actions of (2R,6R)-HNK. The antidepressant actions of (2R,6R)-HNK are blocked in mice with a knockin of the BDNF Val66Met allele (which blocks the processing and activity-dependent release of BDNF) or by intra-mPFC microinjection of an anti-BDNF neutralizing antibody. Blockade of L-type voltage-dependent Ca2+ channels (VDCCs), required for activity-dependent BDNF release, also blocks the actions of (2R,6R)-HNK. Intra-mPFC infusion of pharmacol. inhibitors of TrkB or mTORC1 signaling, which are downstream of BDNF, also block the actions of (2R,6R)-HNK. Moreover, (2R,6R)-HNK increases synaptic function in the mPFC. These findings indicate that activity-dependent BDNF release and downstream TrkB and mTORC1 signaling, which increase synaptic function in the mPFC, are required for the rapid and long-lasting antidepressant effects of (2R,6R)-HNK, supporting the potential use of this metabolite for the treatment of MDD.
  15. 15
    Eckenhoff, R. G., Xi, J., Shimaoka, M., Bhattacharji, A., Covarrubias, M., and Dailey, W. P. (2010) Azi-Isoflurane, a Photolabel Analog of the Commonly Used Inhaled General Anesthetic Isoflurane. ACS Chem. Neurosci. 1 (2), 139– 145,  DOI: 10.1021/cn900014m
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    15
    Azi-isoflurane, a Photolabel Analog of the Commonly Used Inhaled General Anesthetic Isoflurane
    Eckenhoff, Roderic G.; Xi, Jin; Shimaoka, Motomu; Bhattacharji, Aditya; Covarrubias, Manuel; Dailey, William P.
    ACS Chemical Neuroscience (2010), 1 (2), 139-145CODEN: ACNCDM; ISSN:1948-7193. (American Chemical Society)
    Volatility and low-affinity hamper an ability to define mol. targets of the inhaled anesthetics. Photolabels have proven to be a useful approach in this regard, although none have closely mimicked contemporary drugs. The authors report the synthesis and validation of azi-isoflurane, a compd. constructed by adding a diazirinyl moiety to the Me carbon of the commonly used general anesthetic isoflurane. Azi-isoflurane is slightly more hydrophobic than isoflurane, and more potent in tadpoles. This novel compd. inhibits Shaw2 K+ channel currents similarly to isoflurane and binds to apoferritin with enhanced affinity. Finally, when irradiated at 300 nm, azi-isoflurane adducts to residues known to line isoflurane-binding sites in apoferritin and integrin LFA-1, the only proteins with isoflurane binding sites defined by crystallog. This reagent should allow rapid discovery of isoflurane mol. targets and binding sites within those targets.
  16. 16
    Woll, K. A., Peng, W., Liang, Q., Zhi, L., Jacobs, J. A., Maciunas, L., Bhanu, N., Garcia, B. A., Covarrubias, M., Loll, P. J., Dailey, W. P., and Eckenhoff, R. G. (2017) Photoaffinity Ligand for the Inhalational Anesthetic Sevoflurane Allows Mechanistic Insight into Potassium Channel Modulation. ACS Chem. Biol. 12 (5), 1353– 1362,  DOI: 10.1021/acschembio.7b00222
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    16
    Photoaffinity Ligand for the Inhalational Anesthetic Sevoflurane Allows Mechanistic Insight into Potassium Channel Modulation
    Woll, Kellie A.; Peng, Wesley; Liang, Qiansheng; Zhi, Lianteng; Jacobs, Jack A.; Maciunas, Lina; Bhanu, Natarajan; Garcia, Benjamin A.; Covarrubias, Manuel; Loll, Patrick J.; Dailey, William P.; Eckenhoff, Roderic G.
    ACS Chemical Biology (2017), 12 (5), 1353-1362CODEN: ACBCCT; ISSN:1554-8929. (American Chemical Society)
    Sevoflurane is a commonly used inhaled general anesthetic. Despite this, its mechanism of action remains largely elusive. Compared to other anesthetics, sevoflurane exhibits distinct functional activity. In particular, sevoflurane is a pos. modulator of voltage-gated Shaker-related potassium channels (Kv1.x), which are key regulators of action potentials. Here, we report the synthesis and validation of azisevoflurane, a photoaffinity ligand for the direct identification of sevoflurane binding sites in the Kv1.2 channel. Azisevoflurane retains major sevoflurane protein binding interactions and pharmacol. properties within in vivo models. Photoactivation of azisevoflurane induces adduction to amino acid residues that accurately reported sevoflurane protein binding sites in model proteins. Pharmacol. relevant concns. of azisevoflurane analogously potentiated wild-type Kv1.2 and the established mutant Kv1.2 G329T. In wild-type Kv1.2 channels, azisevoflurane photolabeled Leu317 within the internal S4-S5 linker, a vital helix that couples the voltage sensor to the pore region. A residue lining the same binding cavity was photolabeled by azisevoflurane and protected by sevoflurane in the Kv1.2 G329T. Mutagenesis of Leu317 in WT Kv1.2 abolished sevoflurane voltage-dependent pos. modulation. Azisevoflurane addnl. photolabeled a second distinct site at Thr384 near the external selectivity filter in the Kv1.2 G329T mutant. The identified sevoflurane binding sites are located in crit. regions involved in gating of Kv channels and related ion channels. Azisevoflurane has thus emerged as a new tool to discover inhaled anesthetic targets and binding sites and investigate contributions of these targets to general anesthesia.
  17. 17
    Vedula, L. S., Brannigan, G., Economou, N. J., Xi, J., Hall, M. A., Liu, R., Rossi, M. J., Dailey, W. P., Grasty, K. C., Klein, M. L., Eckenhoff, R. G., and Loll, P. J. (2009) A Unitary Anesthetic Binding Site at High Resolution. J. Biol. Chem. 284 (36), 24176– 24184,  DOI: 10.1074/jbc.M109.017814
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    A Unitary Anesthetic Binding Site at High Resolution
    Vedula, L. Sangeetha; Brannigan, Grace; Economou, Nicoleta J.; Xi, Jin; Hall, Michael A.; Liu, Renyu; Rossi, Matthew J.; Dailey, William P.; Grasty, Kimberly C.; Klein, Michael L.; Eckenhoff, Roderic G.; Loll, Patrick J.
    Journal of Biological Chemistry (2009), 284 (36), 24176-24184CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)
    Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABAA receptor, but such receptor-channel complexes remain challenging to study at at. resoln. Until structural biol. methods advance to the point of being able to deal with systems such as the GABAA receptor, it will be necessary to use more tractable surrogates to probe the mol. details of anesthetic recognition. The authors have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clin. relevant protein targets; apoferritin also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABAA receptors, validating this model system for injectable anesthetics. High resoln. x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Mol. dynamics simulations indicate that the ligands undergo considerable fluctuations about their equil. positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiol. targets like ion channels.
  18. 18
    Oakley, S., Vedula, L. S., Bu, W., Meng, Q. C., Xi, J., Liu, R., Eckenhoff, R. G., and Loll, P. J. (2012) Recognition of Anesthetic Barbiturates by a Protein Binding Site: A High Resolution Structural Analysis. PLoS One 7 (2), e32070  DOI: 10.1371/journal.pone.0032070
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    18
    Recognition of anesthetic barbiturates by a protein binding site: a high resolution structural analysis
    Oakley, Simon; Vedula, L. Sangeetha; Bu, Weiming; Meng, Qing Cheng; Xi, Jin; Liu, Renyu; Eckenhoff, Roderic G.; Loll, Patrick J.
    PLoS One (2012), 7 (2), e32070CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)
    Barbiturates potentiate GABA actions at the GABAA receptor and act as central nervous system depressants that can induce effects ranging from sedation to general anesthesia. No structural information has been available about how barbiturates are recognized by their protein targets. For this reason, we tested whether these drugs were able to bind specifically to horse spleen apoferritin, a model protein that has previously been shown to bind many anesthetic agents with affinities that are closely correlated with anesthetic potency. Thiopental, pentobarbital, and phenobarbital were all found to bind to apoferritin with affinities ranging from 10-500 μM, approx. matching the concns. required to produce anesthetic and GABAergic responses. X-ray crystal structures were detd. for the complexes of apoferritin with thiopental and pentobarbital at resolns. of 1.9 and 2.0 Å, resp. These structures reveal that the barbiturates bind to a cavity in the apoferritin shell that also binds haloalkanes, halogenated ethers, and propofol. Unlike these other general anesthetics, however, which rely entirely upon van der Waals interactions and the hydrophobic effect for recognition, the barbiturates are recognized in the apoferritin site using a mixt. of both polar and nonpolar interactions. These results suggest that any protein binding site that is able to recognize and respond to the chem. and structurally diverse set of compds. used as general anesthetics is likely to include a versatile mixt. of both polar and hydrophobic elements.
  19. 19
    Butts, C. A., Xi, J., Brannigan, G., Saad, A. A., Venkatachalan, S. P., Pearce, R. A., Klein, M. L., Eckenhoff, R. G., and Dmochowski, I. J. (2009) Identification of a Fluorescent General Anesthetic, 1-Aminoanthracene. Proc. Natl. Acad. Sci. U. S. A. 106 (16), 6501– 6506,  DOI: 10.1073/pnas.0810590106
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    19
    Identification of a fluorescent general anesthetic, 1-aminoanthracene
    Butts, Christopher A.; Xi, Jin; Brannigan, Grace; Saad, Abdalla A.; Venkatachalan, Srinivasan P.; Pearce, Robert A.; Klein, Michael L.; Eckenhoff, Roderic G.; Dmochowski, Ivan J.
    Proceedings of the National Academy of Sciences of the United States of America (2009), 106 (16), 6501-6506CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    We identified a fluorophore, 1-aminoanthracene (1-AMA), that is anesthetic, potentiates GABAergic transmission, and gives an appropriate dissocn. const., Kd ≈ 0.1 mM, for binding to the general anesthetic site in horse spleen apoferritin (HSAF). 1-AMA fluorescence is enhanced when bound to HSAF. Thus, displacement of 1-AMA from HSAF by other anesthetics attenuates the fluorescence signal and allows detn. of Kd, as validated by isothermal titrn. calorimetry. This provides a unique fluorescence assay for compd. screening and anesthetic discovery. Addnl. electrophysiol. expts. in isolated cells indicate that 1-AMA potentiates chloride currents elicited by GABA, similar to many general anesthetics. Furthermore, 1-AMA reversibly immobilizes stage 45-50 Xenopus laevis tadpoles (EC50 = 16 μM) and fluorescence micrographs show 1-AMA localized to brain and olfactory regions. Thus, 1-AMA provides an unprecedented opportunity for studying general anesthetic distribution in vivo at the cellular and subcellular levels.
  20. 20
    Cohen, M. L. and Trevor, A. J. (1974) On the Cerebral Accumulation of Ketamine and the Relationship Between Metabolism of the Drug and Its Pharmacological Effects. J. Pharmacol. Exp. Ther. 189 (2), 351– 358
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    Cerebral accumulation of ketamine and the relation between metabolism of the drug and its pharmacological effects
    Cohen, Marlene L.; Trevor, Anthony J.
    Journal of Pharmacology and Experimental Therapeutics (1974), 189 (2), 351-8CODEN: JPETAB; ISSN:0022-3565.
    Rat brain slices accumulated and retained ketamine-HCl [1867-66-9] at concns. 2.3 times higher than those in the incubation medium. No selective binding of ketamine to subcellular components of rat brain homogenates was obsd. Detn. of the partition coeffs. of ketamine and its N-demethylated product (metabolite I)) indicated that both compds. were highly lipid sol. The i.v. injection of metabolite I into rats caused central nervous system effects including hypnosis, ataxia, and agitation, but of shorter duration than equiv. doses of ketamine. The pretreatment of rats with phenobarbital caused a 5-fold increase in the rats of ketamine metab. by hepatic tissue in vitro, whereas SKF 525A pretreatment inhibited ketamine metab. by 35% and prolonged the half-life of the drug in vivo.
  21. 21
    Onufriev, A. V. and Alexov, E. (2013) Protonation and PK Changes in Protein-Ligand Binding. Q. Rev. Biophys. 46 (2), 181– 209,  DOI: 10.1017/S0033583513000024
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    21
    Protonation and pK changes in protein-ligand binding
    Onufriev, Alexey V.; Alexov, Emil
    Quarterly Reviews of Biophysics (2013), 46 (2), 181-209CODEN: QURBAW; ISSN:0033-5835. (Cambridge University Press)
    A review. Formation of protein-ligand complexes causes various changes in both the receptor and the ligand. This review focuses on changes in pK and protonation states of ionizable groups that accompany protein-ligand binding. Phys. origins of these effects are outlined, followed by a brief overview of the computational methods to predict them and the assocd. corrections to receptor-ligand binding affinities. Statistical prevalence, magnitude and spatial distribution of the pK and protonation state changes in protein-ligand binding are discussed in detail, based on both exptl. and theor. studies. While there is no doubt that these changes occur, they do not occur all the time; the estd. prevalence varies, both between individual complexes and by method. The changes occur not only in the immediate vicinity of the interface but also sometimes far away. When receptor-ligand binding is assocd. with protonation state change at particular pH, the binding becomes pH dependent: we review the interplay between sub-cellular characteristic pH and optimum pH of receptor-ligand binding. It is pointed out that there is a tendency for protonation state changes upon binding to be minimal at physiol. relevant pH for each complex (no net proton uptake/release), suggesting that native receptor-ligand interactions have evolved to reduce the energy cost assocd. with ionization changes. As a result, previously reported statistical prevalence of these changes - typically computed at the same pH for all complexes - may be higher than what may be expected at optimum pH specific to each complex. We also discuss whether proper account of protonation state changes appears to improve practical docking and scoring outcomes relevant to structure-based drug design. An overview of some of the existing challenges in the field is provided in conclusion.
  22. 22
    Vardy, E., Mosier, P. D., Frankowski, K. J., Wu, H., Katritch, V., Westkaemper, R. B., Aubé, J., Stevens, R. C., and Roth, B. L. (2013) Chemotype-Selective Modes of Action of κ-Opioid Receptor Agonists. J. Biol. Chem. 288 (48), 34470– 34483,  DOI: 10.1074/jbc.M113.515668
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    22
    Chemotype-selective Modes of Action of κ-Opioid Receptor Agonists
    Vardy, Eyal; Mosier, Philip D.; Frankowski, Kevin J.; Wu, Huixian; Katritch, Vsevolod; Westkaemper, Richard B.; Aube, Jeffrey; Stevens, Raymond C.; Roth, Bryan L.
    Journal of Biological Chemistry (2013), 288 (48), 34470-34483CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)
    The crystal structures of opioid receptors provide a novel platform for inquiry into opioid receptor function. The mol. determinants for activation of the κ-opioid receptor (KOR) were studied using a combination of agonist docking, functional assays, and site-directed mutagenesis. Eighteen positions in the putative agonist binding site of KOR were selected and evaluated for their effects on receptor binding and activation by ligands representing four distinct chemotypes: the peptide dynorphin A(1-17), the arylacetamide U-69593, and the non-charged ligands salvinorin A and the octahydroisoquinolinone carboxamide 1xx. Minimally biased docking of the tested ligands into the antagonist-bound KOR structure generated distinct binding modes, which were then evaluated biochem. and pharmacol. Our anal. identified two types of mutations: those that affect receptor function primarily via ligand binding and those that primarily affect function. The shared and differential mechanisms of agonist binding and activation in KOR are further discussed. Usually, mutations affecting function more than binding were located at the periphery of the binding site and did not interact strongly with the various ligands. Anal. of the crystal structure along with the present results provide fundamental insights into the activation mechanism of the KOR and suggest that "functional" residues, along with water mols. detected in the crystal structure, may be directly involved in transduction of the agonist binding event into structural changes at the conserved rotamer switches, thus leading to receptor activation.
  23. 23
    Hustveit, O., Maurset, A., and Oye, I. (1995) Interaction of the Chiral Forms of Ketamine with Opioid, Phencyclidine, Sigma and Muscarinic Receptors. Pharmacol. Toxicol. 77 (6), 355– 359,  DOI: 10.1111/j.1600-0773.1995.tb01041.x
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    23
    Interaction of the chiral forms of ketamine with opioid, phencyclidine, σ and muscarinic receptors
    Hustveit, Olav; Maurset, Atle; Oeye, Ivar
    Pharmacology & Toxicology (Copenhagen) (1995), 77 (6), 355-9CODEN: PHTOEH; ISSN:0901-9928. (Munksgaard)
    To elucidate the mechanisms of action of ketamine, the authors have investigated the binding of the chiral forms of ketamine to opioid (μ, δ and κ), phencyclidine, σ and muscarinic receptors and the authors have performed detailed concn.-response expts. in the guinea-pig ileum prepn. The affinity ratios for the chiral forms at phencyclidine, μ and κ receptors correlated with the potency ratio of the chiral forms in the ischemic pain test found previously. The affinities were highest for phencyclidine receptors. The affinities for muscarinic receptors were lower than for phencyclidine receptors by a factor of about 10-20. The concn.-response expts. revealed one opioid (naloxone sensitive) and one non-opioid component. The two components are very close, which explains why other authors have reported that naloxone antagonizes the ketamine effect only partly. The concns. of naloxone necessary to shift the opioid part of the curves indicate that ketamine is a κ agonist in the guinea-pig ileum prepn. The authors conclude that the analgesic effect of ketamine in humans is most probably mediated via phencyclidine receptors, although a κ effect can not be excluded. Binding to κ and muscarinic receptors may contribute to the psychotomimetic side effects seen during recovery from ketamine anesthesia.
  24. 24
    La Regina, A., Petrillo, P., Sbacchi, M., and Tavani, A. (1988) Interaction of U-69,593 with Mu-, Alpha- and Kappa-Opioid Binding Sites and Its Analgesic and Intestinal Effects in Rats. Life Sci. 42 (3), 293– 301,  DOI: 10.1016/0024-3205(88)90638-8
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    24
    Interaction of U-69,593 with μ-, δ- and κ-opioid binding sites and its analgesic and intestinal effects in rats
    La Regina, A.; Petrillo, P.; Sbacchi, M.; Tavani, A.
    Life Sciences (1988), 42 (3), 293-301CODEN: LIFSAK; ISSN:0024-3205.
    The κ-opioid compd. U-69,593 was studied in rats in vitro in binding assays to assess its selectivity at the single types of opioid sites and in vivo to assess its analgesic activity and effect on intestinal propulsion. In vitro the U-69,593 inhibition curve of [3H]-(-)-bremazocine binding suppressed at μ- and δ-sites was biphasic and the inhibition const. (Ki) at the high-affinity site (10-18 nM) was 2 orders of magnitude smaller than the Ki at the low-affinity site. The Ki at μ- and .vdelta.-sites were resp. 3.3 and 8.5 μM. Thus [3H]-(-)-bremazocine, suppressed at μ- and δ-sites, may still bind more than 1 site, which U-69,593 might distinguish. In vivo U-69,593 i.p. prolonged the reaction time of rats on a 55° hot-plate and the dose of naloxone required to antagonize this effect was 40 times the dose that antagonized morphine-induced antinociception, suggesting the involvement of the κ-receptor. In the intestinal transit test U-69,593 at doses between 0.5 and 15 mg/kg i.p. only slightly slowed intestinal transit of a charcoal meal in rats with no dose-relation; it partly but significantly antagonized morphine-induced constipation. These results suggest that the κ-type of opioid receptor, with which U-69,593 interacts may induce analgesia, but has no appreciable role in the mechanisms of opioid-induced inhibition of intestinal transit in rats.
  25. 25
    McKinstry-Wu, A. R., Woll, K. A., Joseph, T. T., Bu, W., White, E. R., Bhanu, N. V., Garcia, B. A., Brannigan, G., Dailey, W. P., and Eckenhoff, R. G. (2019) Azi-Medetomidine: Synthesis and Characterization of a Novel A2 Adrenergic Photoaffinity Ligand. ACS Chem. Neurosci. 10 (11), 4716– 4728,  DOI: 10.1021/acschemneuro.9b00484
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    Azi-medetomidine: Synthesis and Characterization of a Novel α2 Adrenergic Photoaffinity Ligand
    McKinstry-Wu, Andrew R.; Woll, Kellie A.; Joseph, Thomas T.; Bu, Weiming; White, E. Railey; Bhanu, Natarajan V.; Garcia, Benjamin A.; Brannigan, Grace; Dailey, William P.; Eckenhoff, Roderic G.
    ACS Chemical Neuroscience (2019), 10 (11), 4716-4728CODEN: ACNCDM; ISSN:1948-7193. (American Chemical Society)
    Agonists at the α2 adrenergic receptor produce sedation, increase focus, provide analgesia, and induce centrally mediated hypotension and bradycardia, yet neither their dynamic interactions with adrenergic receptors nor their modulation of neuronal circuit activity is completely understood. Photoaffinity ligands of α2 adrenergic agonists have the potential both to capture discrete moments of ligand-receptor interactions and to prolong naturalistic drug effects in discrete regions of tissue in vivo. We present here the synthesis and characterization of a novel α2 adrenergic agonist photolabel based on the imidazole medetomidine called azi-medetomidine. Azi-medetomidine shares protein assocn. characteristics with its parent compd. in exptl. model systems and by mol. dynamics simulation of interactions with the α2A adrenergic receptor. Azi-medetomidine acts as an agonist at α2A adrenergic receptors, and produces hypnosis in Xenopus laevis tadpoles. Azi-medetomidine competes with the α2 agonist clonidine at α2A adrenergic receptors, which is potentiated by photolabeling, and azi-medetomidine labels moieties on the α2A adrenergic receptor as detd. by mass spectrometry in a manner consistent with a simulated model. This novel α2 adrenergic agonist photolabel can serve as a powerful tool for in vitro and in vivo investigations of adrenergic signaling.
  26. 26
    Andrade, C. (2017) Ketamine for Depression, 4: In What Dose, at What Rate, by What Route, for How Long, and at What Frequency?. J. Clin. Psychiatry 78 (7), e852  DOI: 10.4088/JCP.17f11738
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    Rasmussen, S. G. F., DeVree, B. T., Zou, Y., Kruse, A. C., Chung, K. Y., Kobilka, T. S., Thian, F. S., Chae, P. S., Pardon, E., Calinski, D., Mathiesen, J. M., Shah, S. T. A., Lyons, J. A., Caffrey, M., Gellman, S. H., Steyaert, J., Skiniotis, G., Weis, W. I., Sunahara, R. K., and Kobilka, B. K. (2011) Crystal Structure of the B2 Adrenergic Receptor-Gs Protein Complex. Nature 477 (7366), 549– 555,  DOI: 10.1038/nature10361
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    Crystal structure of the β2 adrenergic receptor-Gs protein complex
    Rasmussen, Soren G. F.; DeVree, Brian T.; Zou, Yao-Zhong; Kruse, Andrew C.; Chung, Ka-Young; Kobilka, Tong-Sun; Thian, Foon-Sun; Chae, Pil-Seok; Pardon, Els; Calinski, Diane; Mathiesen, Jesper M.; Shah, Syed T. A.; Lyons, Joseph A.; Caffrey, Martin; Gellman, Samuel H.; Steyaert, Jan; Skiniotis, Georgios; Weis, William I.; Sunahara, Roger K.; Kobilka, Brian K.
    Nature (London, United Kingdom) (2011), 477 (7366), 549-555CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
    G protein-coupled receptors (GPCRs) are responsible for the majority of cellular responses to hormones and neurotransmitters as well as the senses of sight, olfaction and taste. The paradigm of GPCR signalling is the activation of a heterotrimeric GTP binding protein (G protein) by an agonist-occupied receptor. The β2 adrenergic receptor (β2AR) activation of Gs, the stimulatory G protein for adenylyl cyclase, has long been a model system for GPCR signalling. Here we present the crystal structure of the active state ternary complex composed of agonist-occupied monomeric β2AR and nucleotide-free Gs heterotrimer. The principal interactions between the β2AR and Gs involve the amino- and carboxy-terminal α-helixes of Gs, with conformational changes propagating to the nucleotide-binding pocket. The largest conformational changes in the β2AR include a 14 Å outward movement at the cytoplasmic end of transmembrane segment 6 (TM6) and an α-helical extension of the cytoplasmic end of TM5. The most surprising observation is a major displacement of the α-helical domain of Gαs relative to the Ras-like GTPase domain. This crystal structure represents the first high-resoln. view of transmembrane signalling by a GPCR.
  28. 28
    Koehl, A., Hu, H., Maeda, S., Zhang, Y., Qu, Q., Paggi, J. M., Latorraca, N. R., Hilger, D., Dawson, R., Matile, H., Schertler, G. F. X., Granier, S., Weis, W. I., Dror, R. O., Manglik, A., Skiniotis, G., and Kobilka, B. K. (2018) Structure of the M-Opioid Receptor-G i Protein Complex. Nature 558 (7711), 547,  DOI: 10.1038/s41586-018-0219-7
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    28
    Structure of the μ-opioid receptor-Gi protein complex
    Koehl, Antoine; Hu, Hongli; Maeda, Shoji; Zhang, Yan; Qu, Qianhui; Paggi, Joseph M.; Latorraca, Naomi R.; Hilger, Daniel; Dawson, Roger; Matile, Hugues; Schertler, Gebhard F. X.; Granier, Sebastien; Weis, William I.; Dror, Ron O.; Manglik, Aashish; Skiniotis, Georgios; Kobilka, Brian K.
    Nature (London, United Kingdom) (2018), 558 (7711), 547-552CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
    The μ-opioid receptor (μOR) is a G-protein-coupled receptor (GPCR) and the target of most clin. and recreationally used opioids. The induced pos. effects of analgesia and euphoria are mediated by μOR signalling through the adenylyl cyclase-inhibiting heterotrimeric G protein Gi. Here we present the 3.5 Å resoln. cryo-electron microscopy structure of the μOR bound to the agonist peptide DAMGO and nucleotide-free Gi. DAMGO occupies the morphinan ligand pocket, with its N terminus interacting with conserved receptor residues and its C terminus engaging regions important for opioid-ligand selectivity. Comparison of the μOR-Gi complex to previously detd. structures of other GPCRs bound to the stimulatory G protein Gs reveals differences in the position of transmembrane receptor helix 6 and in the interactions between the G protein α-subunit and the receptor core. Together, these results shed light on the structural features that contribute to the Gi protein-coupling specificity of the μOR.
  29. 29
    Suomivuori, C.-M., Latorraca, N. R., Wingler, L. M., Eismann, S., King, M. C., Kleinhenz, A. L. W., Skiba, M. A., Staus, D. P., Kruse, A. C., Lefkowitz, R. J., and Dror, R. O. (2020) Molecular Mechanism of Biased Signaling in a Prototypical G Protein-Coupled Receptor. Science 367 (6480), 881– 887,  DOI: 10.1126/science.aaz0326
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    Molecular mechanism of biased signaling in a prototypical G protein-coupled receptor
    Suomivuori, Carl-Mikael; Latorraca, Naomi R.; Wingler, Laura M.; Eismann, Stephan; King, Matthew C.; Kleinhenz, Alissa L. W.; Skiba, Meredith A.; Staus, Dean P.; Kruse, Andrew C.; Lefkowitz, Robert J.; Dror, Ron O.
    Science (Washington, DC, United States) (2020), 367 (6480), 881-887CODEN: SCIEAS; ISSN:1095-9203. (American Association for the Advancement of Science)
    Biased signaling, in which different ligands that bind to the same G protein-coupled receptor preferentially trigger distinct signaling pathways, holds great promise for the design of safer and more effective drugs. Its structural mechanism remains unclear, however, hampering efforts to design drugs with desired signaling profiles. Here, we use extensive at.-level mol. dynamics simulations to det. how arrestin bias and G protein bias arise at the angiotensin II type 1 receptor. The receptor adopts two major signaling conformations, one of which couples almost exclusively to arrestin, whereas the other also couples effectively to a G protein. A long-range allosteric network allows ligands in the extracellular binding pocket to favor either of the two intracellular conformations. Guided by this computationally detd. mechanism, we designed ligands with desired signaling profiles.
  30. 30
    Yang, C., Kobayashi, S., Nakao, K., Dong, C., Han, M., Qu, Y., Ren, Q., Zhang, J., Ma, M., Toki, H., Yamaguchi, J., Chaki, S., Shirayama, Y., Nakazawa, K., Manabe, T., and Hashimoto, K. (2018) AMPA Receptor Activation-Independent Antidepressant Actions of Ketamine Metabolite (S)-Norketamine. Biol. Psychiatry 84 (8), 591– 600,  DOI: 10.1016/j.biopsych.2018.05.007
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    AMPA Receptor Activation-Independent Antidepressant Actions of Ketamine Metabolite (S)-Norketamine
    Yang, Chun; Kobayashi, Shizuka; Nakao, Kazuhito; Dong, Chao; Han, Mei; Qu, Youge; Ren, Qian; Zhang, Ji-chun; Ma, Min; Toki, Hidetoh; Yamaguchi, Jun-ichi; Chaki, Shigeyuki; Shirayama, Yukihiko; Nakazawa, Kazu; Manabe, Toshiya; Hashimoto, Kenji
    Biological Psychiatry (2018), 84 (8), 591-600CODEN: BIPCBF; ISSN:0006-3223. (Elsevier)
    Background: Ketamine, an N-methyl-D-aspartate receptor antagonist, exerts robust antidepressant effects in patients with treatment-resistant depression. The precise mechanisms underlying ketamine's antidepressant actions remain unclear, although previous research suggests that alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) activation plays a role. We investigated whether (S)-norketamine and (R)-norketamine, the two main metabolites of (R,S)-ketamine, also play a significant role in ketamine's antidepressant effects and whether the effects are mediated by AMPAR. Methods: Cellular mechanisms of antidepressant action of norketamine enantiomers were examd. in mice. Results: (S)-Norketamine had more potent antidepressant effects than (R)-norketamine in inflammation and chronic social defeat stress models. Furthermore, (S)-norketamine induced more beneficial effects on decreased dendritic spine d. and synaptogenesis in the prefrontal cortex and hippocampus compared with (R)-norketamine. Unexpectedly, AMPAR antagonists did not block the antidepressant effects of (S)-norketamine. The electrophysiol. data showed that, although (S)-norketamine inhibited N-methyl-D-aspartate receptor-mediated synaptic currents, (S)-norketamine did not enhance AMPAR-mediated neurotransmission in hippocampal neurons. Furthermore, (S)-norketamine improved redns. in brain-derived neurotrophic factor-tropomyosin receptor kinase B signaling in the prefrontal cortex of mice susceptible to chronic social defeat stress, whereas the tropomyosin receptor kinase B antagonist and a mechanistic target of rapamycin inhibitor blocked the antidepressant effects of (S)-norketamine. In contrast to (S)-ketamine, (S)-norketamine did not cause behavioral abnormalities, such as prepulse inhibition deficits, reward effects, loss of parvalbumin immunoreactivity in the medial prefrontal cortex, or baseline gamma-band oscillation increase. Conclusions: Our data identified a novel AMPAR activation-independent mechanism underlying the antidepressant effects of (S)-norketamine. (S)-Norketamine and its prodrugs could be novel antidepressants without the detrimental side effects of (S)-ketamine.
  31. 31
    Yokoyama, R., Higuchi, M., Tanabe, W., Tsukada, S., Naito, M., Yamaguchi, T., Chen, L., Kasai, A., Seiriki, K., Nakazawa, T., Nakagawa, S., Hashimoto, K., Hashimoto, H., and Ago, Y. (2020) (S)-Norketamine and (2S,6S)-Hydroxynorketamine Exert Potent Antidepressant-like Effects in a Chronic Corticosterone-Induced Mouse Model of Depression. Pharmacol., Biochem. Behav. 191, 172876,  DOI: 10.1016/j.pbb.2020.172876
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    (S)-norketamine and (2S,6S)-hydroxynorketamine exert potent antidepressant-like effects in a chronic corticosterone-induced mouse model of depression
    Yokoyama, Rei; Higuchi, Momoko; Tanabe, Wataru; Tsukada, Shinji; Naito, Megumi; Yamaguchi, Takumi; Chen, Lu; Kasai, Atsushi; Seiriki, Kaoru; Nakazawa, Takanobu; Nakagawa, Shinsaku; Hashimoto, Kenji; Hashimoto, Hitoshi; Ago, Yukio
    Pharmacology, Biochemistry and Behavior (2020), 191 (), 172876CODEN: PBBHAU; ISSN:0091-3057. (Elsevier)
    Clin. and preclin. studies have shown that the N-methyl-D-aspartate receptor antagonist ketamine exerts rapid and long-lasting antidepressant effects. Although ketamine metabolites might also have potential antidepressant properties, controversial results have been reported for (2R,6R)-hydroxynorketamine ((2R,6R)-HNK) in particular, and there is little information regarding the effects of other ketamine metabolites. Here we aimed to compare the effects of (R)-norketamine ((R)-NK), (S)-NK, (2R,6R)-HNK, and (2S,6S)-HNK in a mouse model of depression induced by chronic corticosterone (CORT) injection. None of the ketamine metabolites at doses up to 20 mg/kg showed antidepressant-like activity in naive male C57BL6/J mice. Chronic CORT treatment increased immobility in the forced swim test and caused anhedonic-like behaviors in the female encounter test. A single administration of (S)-NK and (2S,6S)-HNK dose-dependently reduced the enhanced immobility at 30 min after injection in chronic CORT-treated mice, while (R)-NK or (2R,6R)-HNK did not. Addnl., (S)-NK and (2S,6S)-HNK, but not (R)-NK or (2R,6R)-HNK, improved chronic CORT-induced anhedonia at 24 h after the injection. These results suggest that (S)-ketamine metabolites (S)-NK and (2S,6S)-HNK have potent acute and sustained antidepressant effects in rodents.
  32. 32
    Cui, X., Yeliseev, A., and Liu, R. (2013) Ligand Interaction, Binding Site and G Protein Activation of the Mu Opioid Receptor. Eur. J. Pharmacol. 702 (1–3), 309– 315,  DOI: 10.1016/j.ejphar.2013.01.060
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    Ligand interaction, binding site and G protein activation of the mu opioid receptor
    Cui, Xu; Yeliseev, Alexei; Liu, Renyu
    European Journal of Pharmacology (2013), 702 (1-3), 309-315CODEN: EJPHAZ; ISSN:0014-2999. (Elsevier B.V.)
    With the recently solved crystal structure of the murine mu opioid receptor, the elucidation of the structure function relationships of the human mu receptor becomes feasible. In this study, we analyzed the available structural information along with ligand binding and G protein activation of human mu receptor. Affinity detns. were performed in a HEK293 cell line stably transfected with the human mu opioid receptor for 6 different agonists (morphine, DAMGO, and herkinorn) and antagonists (naloxone, beta-Funaltrexamine, and Norbinaltorphimine). G protein activation was investigated in membrane prepns. contg. human mu receptors treated with the agonist, partial agonist, or antagonist compds. 4DKL.pdb was utilized for structural anal. and docking calcns. for 28 mu receptor ligands. The predicted affinities from docking were compared with those exptl. detd. While all known ligands bind to the receptor through the same binding site that is large enough to accommodate mols. of various sizes, interaction with D147 (D149 in human mu receptor) is essential for binding. No distinguishable interaction pattern in the binding site for agonist, partial agonist, or antagonist to predict pharmacol. activities was found. The failure to reconcile the predicted affinities from docking with exptl. values indicates that the receptor might undergo significant conformational changes from one state to the other states upon different ligand binding. A simplified model to understand the complicated system is proposed and further study on these multiple conformations using high resoln. structural approaches is suggested.
  33. 33
    Mafi, A., Kim, S.-K., and Goddard, W. A. (2020) The Atomistic Level Structure for the Activated Human κ-Opioid Receptor Bound to the Full Gi Protein and the MP1104 Agonist. Proc. Natl. Acad. Sci. U. S. A. 117 (11), 5836– 5843,  DOI: 10.1073/pnas.1910006117
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    The atomistic level structure for the activated human κ-opioid receptor bound to the full Gi protein and the MP1104 agonist
    Mafi, Amirhossein; Kim, Soo-Kyung; Goddard, William A., III
    Proceedings of the National Academy of Sciences of the United States of America (2020), 117 (11), 5836-5843CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    The kappa opioid receptor (kOR) is an important target for pain therapeutics to reduce depression and other harmful side effects of existing medications. The analgesic activity is mediated by kOR signaling through the adenylyl cyclase-inhibitory family of Gi protein. Here, we report the three-dimensional (3D) structure for the active state of human kOR complexed with both heterotrimeric Gi protein and MP1104 agonist. This structure resulted from long mol. dynamics (MD) and metadynamics (metaMD) simulations starting from the 3.1-Å X-ray structure of kOR-MP1104 after replacing the nanobody with the activated Gi protein and from the 3.5-Å cryo-EM structure of μOR-Gi complex after replacing the 168 missing residues. Using MD and metaMD we discovered interactions to the Gi protein with strong anchors to two intracellular loops and transmembrane helix 6 of the kOR. These anchors strengthen the binding, contributing to a contraction in the binding pocket but an expansion in the cytoplasmic region of κOR to accommodate G protein. These remarkable changes in κOR structure reveal that the anchors are essential for activation.
  34. 34
    Yamaguchi, J., Toki, H., Qu, Y., Yang, C., Koike, H., Hashimoto, K., Mizuno-Yasuhira, A., and Chaki, S. (2018) (2 R,6 R)-Hydroxynorketamine Is Not Essential for the Antidepressant Actions of (R)-Ketamine in Mice. Neuropsychopharmacology 43 (9), 1900– 1907,  DOI: 10.1038/s41386-018-0084-y
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    (2R,6R)-Hydroxynorketamine is not essential for the antidepressant actions of (R)-ketamine in mice
    Yamaguchi, Jun-ichi; Toki, Hidetoh; Qu, Youge; Yang, Chun; Koike, Hiroyuki; Hashimoto, Kenji; Mizuno-Yasuhira, Akiko; Chaki, Shigeyuki
    Neuropsychopharmacology (2018), 43 (9), 1900-1907CODEN: NEROEW; ISSN:0893-133X. (Nature Research)
    (R,S)-Ketamine has rapid and sustained antidepressant effects in depressed patients. Although the metab. of (R,S)-ketamine to (2 R,6 R)-hydroxynorketamine (HNK), a metabolite of (R)-ketamine, has been reported to be essential for its antidepressant effects, recent evidence suggests otherwise. The present study investigated the role of the metab. of (R)-ketamine to (2 R,6 R)-HNK in the antidepressant actions of (R)-ketamine. Antidepressant effects were evaluated using the forced swimming test in the lipopolysaccharide (LPS)-induced inflammation model of mice and the tail suspension test in naive mice. To prevent the metab. of (R)-ketamine to (2 R,6 R)-HNK, mice were pretreated with cytochrome P 450 (CYP) inhibitors. The concns. of (R)-ketamine, (R)-norketamine, and (2 R,6 R)-HNK in plasma, brain, and cerebrospinal fluid (CSF) samples were detd. using enantioselective liq. chromatog.-tandem mass spectrometry. The concns. of (R)-norketamine and (2 R,6 R)-HNK in plasma, brain, and CSF samples after administration of (R)-norketamine (10 mg/kg) and (2 R,6 R)-HNK (10 mg/kg), resp., were higher than those generated after administration of (R)-ketamine (10 mg/kg). Nonetheless, while (R)-ketamine attenuated, neither (R)-norketamine nor (2 R,6 R)-HNK significantly altered immobility times of LPS-treated mice. Treatment with CYP inhibitors prior to administration of (R)-ketamine increased the plasma levels of (R)-ketamine, while generation of (2 R,6 R)-HNK was almost completely blocked. (R)-Ketamine exerted the antidepressant effects at a lower dose in the presence of CYP inhibitors than in their absence, which is consistent with exposure levels of (R)-ketamine but not (2 R,6 R)-HNK. These results indicate that metab. to (2 R,6 R)-HNK is not necessary for the antidepressant effects of (R)-ketamine and that unmetabolized (R)-ketamine itself may be responsible for its antidepressant actions.
  35. 35
    Zanos, P., Moaddel, R., Morris, P. J., Georgiou, P., Fischell, J., Elmer, G. I., Alkondon, M., Yuan, P., Pribut, H. J., Singh, N. S., Dossou, K. S. S., Fang, Y., Huang, X.-P., Mayo, C. L., Wainer, I. W., Albuquerque, E. X., Thompson, S. M., Thomas, C. J., Zarate, C. A., and Gould, T. D. (2016) NMDAR Inhibition-Independent Antidepressant Actions of Ketamine Metabolites. Nature 533 (7604), 481– 486,  DOI: 10.1038/nature17998
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    NMDAR inhibition-independent antidepressant actions of ketamine metabolites
    Zanos, Panos; Moaddel, Ruin; Morris, Patrick J.; Georgiou, Polymnia; Fischell, Jonathan; Elmer, Greg I.; Alkondon, Manickavasagom; Yuan, Peixiong; Pribut, Heather J.; Singh, Nagendra S.; Dossou, Katina S. S.; Fang, Yuhong; Huang, Xi-Ping; Mayo, Cheryl L.; Wainer, Irving W.; Albuquerque, Edson X.; Thompson, Scott M.; Thomas, Craig J.; Zarate, Carlos A., Jr; Gould, Todd D.
    Nature (London, United Kingdom) (2016), 533 (7604), 481-486CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
    Major depressive disorder affects around 16% of the world population at some point in their lives. Despite the availability of numerous monoaminergic-based antidepressants, most patients require several weeks, if not months, to respond to these treatments, and many patients never attain sustained remission of their symptoms. The noncompetitive, glutamatergic NMDAR (N-methyl-D-aspartate receptor) antagonist (R,S)-ketamine exerts rapid and sustained antidepressant effects after a single dose in patients with depression, but its use is assocd. with undesirable side effects. Here the authors show that the metab. of (R,S)-ketamine to (2S,6S;2R,6R)-hydroxynorketamine (HNK) is essential for its antidepressant effects, and that the (2R,6R)-HNK enantiomer exerts behavioral, electroencephalog., electrophysiol. and cellular antidepressant-related actions in mice. These antidepressant actions are independent of NMDAR inhibition but involve early and sustained activation of AMPARs (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors). The authors also establish that (2R,6R)-HNK lacks ketamine-related side effects. The data implicate a novel mechanism underlying the antidepressant properties of (R,S)-ketamine and have relevance for the development of next-generation, rapid-acting antidepressants.
  36. 36
    Lumsden, E. W., Troppoli, T. A., Myers, S. J., Zanos, P., Aracava, Y., Kehr, J., Lovett, J., Kim, S., Wang, F.-H., Schmidt, S., Jenne, C. E., Yuan, P., Morris, P. J., Thomas, C. J., Zarate, C. A., Moaddel, R., Traynelis, S. F., Pereira, E. F. R., Thompson, S. M., Albuquerque, E. X., and Gould, T. D. (2019) Antidepressant-Relevant Concentrations of the Ketamine Metabolite (2R,6R)-Hydroxynorketamine Do Not Block NMDA Receptor Function. Proc. Natl. Acad. Sci. U. S. A. 116 (11), 5160– 5169,  DOI: 10.1073/pnas.1816071116
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    Antidepressant-relevant concentrations of the ketamine metabolite (2R,6R)-hydroxynorketamine do not block NMDA receptor function
    Lumsden, Eric W.; Troppoli, Timothy A.; Myers, Scott J.; Zanos, Panos; Aracava, Yasco; Kehr, Jan; Lovett, Jacqueline; Kim, Sukhan; Wang, Fu-Hua; Schmidt, Staffan; Jenne, Carleigh E.; Yuan, Peixiong; Morris, Patrick J.; Thomas, Craig J.; Zarate, Carlos A. Jr.; Moaddel, Ruin; Traynelis, Stephen F.; Pereira, Edna F. R.; Thompson, Scott M.; Albuquerque, Edson X.; Gould, Todd D.
    Proceedings of the National Academy of Sciences of the United States of America (2019), 116 (11), 5160-5169CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    Preclin. studies indicate that (2R,6R)-hydroxynorketamine (HNK) is a putative fast-acting antidepressant candidate. Although inhibition of NMDA-type glutamate receptors (NMDARs) is one mechanism proposed to underlie ketamine antidepressant and adverse effects, the potency of (2R,6R)-HNK to inhibit NMDARs has not been established. We used a multidisciplinary approach to det. the effects of (2R,6R)-HNK on NMDAR function. Antidepressant-relevant behavioral responses and (2R,6R)-HNK levels in the extracellular compartment of the hippocampus were measured following systemic (2R,6R)-HNK administration in mice. The effects of ketamine, (2R,6R)-HNK, and, in some cases, the (2S,6S)-HNK stereoisomer were evaluated on the following: (i) NMDA-induced lethality in mice, (ii) NMDAR-mediated field excitatory postsynaptic potentials (fEPSPs) in the CA1 field of mouse hippocampal slices, (iii) NMDAR-mediated miniature excitatory postsynaptic currents (mEPSCs) and NMDA-evoked currents in CA1 pyramidal neurons of rat hippocampal slices, and (iv) recombinant NMDARs expressed in Xenopus oocytes. While a single i.p. injection of 10 mg/kg (2R,6R)-HNK exerted antidepressant-related behavioral and cellular responses in mice, the ED50 of (2R,6R)-HNK to prevent NMDA-induced lethality was found to be 228 mg/kg, compared with 6.4 mg/kg for ketamine. The 10 mg/kg (2R,6R)-HNK dose generated maximal hippocampal extracellular concns. of 8 μM, which were well below concns. required to inhibit synaptic and extrasynaptic NMDARs in vitro. (2S,6S)-HNK was more potent than (2R,6R)-HNK, but less potent than ketamine at inhibiting NMDARs. These data demonstrate the stereoselectivity of NMDAR inhibition by (2R,6R;2S,6S)-HNK and support the conclusion that direct NMDAR inhibition does not contribute to antidepressant-relevant effects of (2R,6R)-HNK.
  37. 37
    Best, R. B., Zhu, X., Shim, J., Lopes, P. E. M., Mittal, J., Feig, M., and MacKerell, A. D. (2012) Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone ϕ, ψ and Side-Chain X1 and X2 Dihedral Angles. J. Chem. Theory Comput. 8 (9), 3257– 3273,  DOI: 10.1021/ct300400x
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    Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone .vphi., ψ and Side-Chain χ1 and χ2 Dihedral Angles
    Best, Robert B.; Zhu, Xiao; Shim, Jihyun; Lopes, Pedro E. M.; Mittal, Jeetain; Feig, Michael; MacKerell, Alexander D.
    Journal of Chemical Theory and Computation (2012), 8 (9), 3257-3273CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
    While the quality of the current CHARMM22/CMAP additive force field for proteins has been demonstrated in a large no. of applications, limitations in the model with respect to the equil. between the sampling of helical and extended conformations in folding simulations have been noted. To overcome this, as well as make other improvements in the model, we present a combination of refinements that should result in enhanced accuracy in simulations of proteins. The common (non-Gly, -Pro) backbone CMAP potential has been refined against exptl. soln. NMR data for weakly structured peptides, resulting in a rebalancing of the energies of the α-helix and extended regions of the Ramachandran map, correcting the α-helical bias of CHARMM22/CMAP. The Gly and Pro CMAPs have been refitted to more accurate quantum-mech. energy surfaces. Side-chain torsion parameters have been optimized by fitting to backbone-dependent quantum-mech. energy surfaces, followed by addnl. empirical optimization targeting NMR scalar couplings for unfolded proteins. A comprehensive validation of the revised force field was then performed against a collection of exptl. data: (i) comparison of simulations of eight proteins in their crystal environments with crystal structures; (ii) comparison with backbone scalar couplings for weakly structured peptides; (iii) comparison with NMR residual dipolar couplings and scalar couplings for both backbone and side-chains in folded proteins; (iv) equil. folding of mini-proteins. The results indicate that the revised CHARMM 36 parameters represent an improved model for modeling and simulation studies of proteins, including studies of protein folding, assembly, and functionally relevant conformational changes.
  38. 38
    Klauda, J. B., Venable, R. M., Freites, J. A., O’Connor, J. W., Tobias, D. J., Mondragon-Ramirez, C., Vorobyov, I., MacKerell, A. D., and Pastor, R. W. (2010) Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types. J. Phys. Chem. B 114 (23), 7830– 7843,  DOI: 10.1021/jp101759q
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    Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types
    Klauda, Jeffery B.; Venable, Richard M.; Freites, J. Alfredo; O'Connor, Joseph W.; Tobias, Douglas J.; Mondragon-Ramirez, Carlos; Vorobyov, Igor; MacKerell, Alexander D., Jr.; Pastor, Richard W.
    Journal of Physical Chemistry B (2010), 114 (23), 7830-7843CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)
    A significant modification to the additive all-atom CHARMM lipid force field (FF) is developed and applied to phospholipid bilayers with both choline and ethanolamine contg. head groups and with both satd. and unsatd. aliph. chains. Motivated by the current CHARMM lipid FF (C27 and C27r) systematically yielding values of the surface area per lipid that are smaller than exptl. ests. and gel-like structures of bilayers well above the gel transition temp., selected torsional, Lennard-Jones and partial at. charge parameters were modified by targeting both quantum mech. (QM) and exptl. data. QM calcns. ranging from high-level ab initio calcns. on small mols. to semiempirical QM studies on a 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) bilayer in combination with exptl. thermodn. data were used as target data for parameter optimization. These changes were tested with simulations of pure bilayers at high hydration of the following six lipids: DPPC, 1,2-dimyristoyl-sn-phosphatidylcholine (DMPC), 1,2-dilauroyl-sn-phosphatidylcholine (DLPC), 1-palmitoyl-2-oleoyl-sn-phosphatidylcholine (POPC), 1,2-dioleoyl-sn-phosphatidylcholine (DOPC), and 1-palmitoyl-2-oleoyl-sn-phosphatidylethanolamine (POPE); simulations of a low hydration DOPC bilayer were also performed. Agreement with exptl. surface area is on av. within 2%, and the d. profiles agree well with neutron and x-ray diffraction expts. NMR deuterium order parameters (SCD) are well predicted with the new FF, including proper splitting of the SCD for the aliph. carbon adjacent to the carbonyl for DPPC, POPE, and POPC bilayers. The area compressibility modulus and frequency dependence of 13C NMR relaxation rates of DPPC and the water distribution of low hydration DOPC bilayers also agree well with expt. Accordingly, the presented lipid FF, referred to as C36, allows for mol. dynamics simulations to be run in the tensionless ensemble (NPT), and is anticipated to be of utility for simulations of pure lipid systems as well as heterogeneous systems including membrane proteins.
  39. 39
    Vanommeslaeghe, K. and MacKerell, A. D. (2012) Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing. J. Chem. Inf. Model. 52 (12), 3144– 3154,  DOI: 10.1021/ci300363c
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    Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing
    Vanommeslaeghe, K.; MacKerell, A. D.
    Journal of Chemical Information and Modeling (2012), 52 (12), 3144-3154CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Mol. mechanics force fields are widely used in computer-aided drug design for the study of drug-like mols. alone or interacting with biol. systems. In simulations involving biol. macromols., the biol. part is typically represented by a specialized biomol. force field, while the drug is represented by a matching general (org.) force field. In order to apply these general force fields to an arbitrary drug-like mol., functionality for assignment of atom types, parameters, and charges is required. In the present article, which is part I of a series of two, we present the algorithms for bond perception and atom typing for the CHARMM General Force Field (CGenFF). The CGenFF atom typer first assocs. attributes to the atoms and bonds in a mol., such as valence, bond order, and ring membership among others. Of note are a no. of features that are specifically required for CGenFF. This information is then used by the atom typing routine to assign CGenFF atom types based on a programmable decision tree. This allows for straight-forward implementation of CGenFF's complicated atom typing rules and for equally straight-forward updating of the atom typing scheme as the force field grows. The presented atom typer was validated by assigning correct atom types on 477 model compds. including in the training set as well as 126 test-set mols. that were constructed to specifically verify its different components. The program may be utilized via an online implementation at https://www.paramchem.org/.
  40. 40
    Vanommeslaeghe, K., Raman, E. P., and MacKerell, A. D. (2012) Automation of the CHARMM General Force Field (CGenFF) II: Assignment of Bonded Parameters and Partial Atomic Charges. J. Chem. Inf. Model. 52 (12), 3155– 3168,  DOI: 10.1021/ci3003649
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    40
    Automation of the CHARMM General Force Field (CGenFF) II: Assignment of Bonded Parameters and Partial Atomic Charges
    Vanommeslaeghe, K.; Raman, E. Prabhu; MacKerell, A. D.
    Journal of Chemical Information and Modeling (2012), 52 (12), 3155-3168CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    Mol. mechanics force fields are widely used in computer-aided drug design for the study of drug candidates interacting with biol. systems. In these simulations, the biol. part is typically represented by a specialized biomol. force field, while the drug is represented by a matching general (org.) force field. In order to apply these general force fields to an arbitrary drug-like mol., functionality for assignment of atom types, parameters, and partial at. charges is required. In the present article, algorithms for the assignment of parameters and charges for the CHARMM General Force Field (CGenFF) are presented. These algorithms rely on the existing parameters and charges that were detd. as part of the parametrization of the force field. Bonded parameters are assigned based on the similarity between the atom types that define said parameters, while charges are detd. using an extended bond-charge increment scheme. Charge increments were optimized to reproduce the charges on model compds. that were part of the parametrization of the force field. Case studies are presented to clarify the functioning of the algorithms and the significance of their output data.
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    Mayne, C. G., Saam, J., Schulten, K., Tajkhorshid, E., and Gumbart, J. C. (2013) Rapid Parameterization of Small Molecules Using the Force Field Toolkit. J. Comput. Chem. 34 (32), 2757– 2770,  DOI: 10.1002/jcc.23422
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    Rapid parameterization of small molecules using the force field toolkit
    Mayne, Christopher G.; Saam, Jan; Schulten, Klaus; Tajkhorshid, Emad; Gumbart, James C.
    Journal of Computational Chemistry (2013), 34 (32), 2757-2770CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
    The inability to rapidly generate accurate and robust parameters for novel chem. matter continues to severely limit the application of mol. dynamics simulations to many biol. systems of interest, esp. in fields such as drug discovery. Although the release of generalized versions of common classical force fields, for example, General Amber Force Field and CHARMM General Force Field, have posited guidelines for parameterization of small mols., many tech. challenges remain that have hampered their wide-scale extension. The Force Field Toolkit (ffTK), described herein, minimizes common barriers to ligand parameterization through algorithm and method development, automation of tedious and error-prone tasks, and graphical user interface design. Distributed as a VMD plugin, ffTK facilitates the traversal of a clear and organized workflow resulting in a complete set of CHARMM-compatible parameters. A variety of tools are provided to generate quantum mech. target data, setup multidimensional optimization routines, and analyze parameter performance. Parameters developed for a small test set of mols. using ffTK were comparable to existing CGenFF parameters in their ability to reproduce exptl. measured values for pure-solvent properties (<15% error from expt.) and free energy of solvation (±0.5 kcal/mol from expt.). © 2013 Wiley Periodicals, Inc.
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    Joseph, T. T., Hénin, J., Eckenhoff, R. G., and Dmochowski, I. J. (2018) Molecular Mechanics Parameterization of Anesthetic Molecules. Methods in Enzymology 602, 61– 76,  DOI: 10.1016/bs.mie.2018.01.003
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    Molecular mechanics parameterization of anesthetic molecules
    Joseph, Thomas T.; Henin, Jerome
    Methods in Enzymology (2018), 602 (Chemical and Biochemical Approaches for the Study of Anesthetic Function, Part A), 61-76CODEN: MENZAU; ISSN:0076-6879. (Elsevier Inc.)
    A review. Anesthetic drug mols. are being increasingly studied through the use of computational methods such as mol. dynamics (MD). Mol. mechanics force fields require the investigator to supply parameters for the force field equation, which are not available for novel mols. Careful selection of these parameters is crit. for simulations to produce meaningful results. Therefore, this chapter presents a state-of-the-art method for detg. these parameters by comparison to quantum mechanics calcns. and exptl. quantities. Ketamine is used as an example to demonstrate the process.
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    Joback, K. G. and Reid, R. C. (1987) Estimation of Pure-Component Properties from Group-Contributions. Chem. Eng. Commun. 57 (1–6), 233– 243,  DOI: 10.1080/00986448708960487
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    Estimation of pure-component properties from group contributions
    Joback, K. G.; Reid, R. C.
    Chemical Engineering Communications (1987), 57 (1-6), 233-43CODEN: CEGCAK; ISSN:0098-6445.
    For estg. the normal b.p., normal f.p., crit. consts. (temp., pressure, vol.), heat of formation (ideal gas at 298 K), Gibbs free energy of formation (ideal gas, unit fugacity, at 298 K), heat capacity (ideal gas), heat of vaporization (at the normal b.p.), heat of fusion, and liq. viscosity for a wide variety of org. compds., estn. equations for these properties and their numerical parameters (detd. by using existing exptl. data) are given for the contributions from 41 atoms or functional groups (including both ring and nonring increments), corresponding to simple increments of: (a) carbon and carbon-hydrogen groups, (b) halogens, (c) oxygen and oxygen-contg. groups, (d) nitrogen and nitrogen-contg. groups, and (e) sulfur and SH.
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    Harrison, C. and Traynor, J. R. (2003) The [35S]GTPgammaS Binding Assay: Approaches and Applications in Pharmacology. Life Sci. 74 (4), 489– 508,  DOI: 10.1016/j.lfs.2003.07.005
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    The [35S]GTPγS binding assay: approaches and applications in pharmacology
    Harrison, C.; Traynor, J. R.
    Life Sciences (2003), 74 (4), 489-508CODEN: LIFSAK; ISSN:0024-3205. (Elsevier Science Inc.)
    A review. Receptors of the of seven transmembrane spanning, heterotrimeric G protein coupled family (GPCR) play crucial roles in regulating physiol. functions and consequently are targets for the action of many classes of drugs. Activation of receptor by agonist leads to the dissocn. of GDP from Gα of the Gαβγ heterotrimer, followed by the binding of GTP to Gα and subsequent modulation of downstream effectors. The G protein heterotrimer is reformed by GTPase activity of the Gα subunit, forming Gα-GDP and so allowing Gα and Gβγ to recombine. The [35S]GTPγS assay measures the level of G protein activation following agonist occupation of a GPCR, by detg. the binding of the non-hydrolyzable analog [35S]GTPγS to Gα subunits. Thus, the assay measures a functional consequence of receptor occupancy at one of the earliest receptor-mediated events. The assay allows for traditional pharmacol. parameters of potency, efficacy and antagonist affinity, with the advantage that agonist measures are not subjected to amplification or other modulation that may occur when analyzing parameters further downstream of the receptor. In general the assay is exptl. more feasible for receptors coupled to the abundant Gi/o proteins. Nevertheless, [35S]GTPγS binding assays are used with GPCRs that couple to the Gs and Gq families of G proteins, esp. in artificial expression systems, or using receptor-Gα constructs or immunopptn. of [35S]GTPγS-labeled Gα. The relative simplicity of the assay has made it very popular and its use is providing insights into contemporary pharmacol. topics including the roles of accessory proteins in signaling, constitutive activity of receptors and agonist specific signaling.
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    Liu, R., Huang, X.-P., Yeliseev, A., Xi, J., and Roth, B. L. (2014) Novel Molecular Targets of Dezocine and Their Clinical Implications. Anesthesiol. J. Am. Soc. Anesthesiol. 120 (3), 714– 723,  DOI: 10.1097/ALN.0000000000000076
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    Kroeze, W. K., Sassano, M. F., Huang, X.-P., Lansu, K., McCorvy, J. D., Giguère, P. M., Sciaky, N., and Roth, B. L. (2015) PRESTO-Tango as an Open-Source Resource for Interrogation of the Druggable Human GPCRome. Nat. Struct. Mol. Biol. 22 (5), 362– 369,  DOI: 10.1038/nsmb.3014
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    PRESTO-Tango as an open-source resource for interrogation of the druggable human GPCRome
    Kroeze, Wesley K.; Sassano, Maria F.; Huang, Xi-Ping; Lansu, Katherine; McCorvy, John D.; Giguere, Patrick M.; Sciaky, Noah; Roth, Bryan L.
    Nature Structural & Molecular Biology (2015), 22 (5), 362-369CODEN: NSMBCU; ISSN:1545-9993. (Nature Publishing Group)
    G protein-coupled receptors (GPCRs) are essential mediators of cellular signaling and are important targets of drug action. Of the approx. 350 nonolfactory human GPCRs, more than 100 are still considered to be 'orphans' because their endogenous ligands remain unknown. Here, we describe a unique open-source resource that allows interrogation of the druggable human GPCRome via a G protein-independent β-arrestin-recruitment assay. We validate this unique platform at more than 120 nonorphan human GPCR targets, demonstrate its utility for discovering new ligands for orphan human GPCRs and describe a method (parallel receptorome expression and screening via transcriptional output, with transcriptional activation following arrestin translocation (PRESTO-Tango)) for the simultaneous and parallel interrogation of the entire human nonolfactory GPCRome.
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    Huang, W., Manglik, A., Venkatakrishnan, A. J., Laeremans, T., Feinberg, E. N., Sanborn, A. L., Kato, H. E., Livingston, K. E., Thorsen, T. S., Kling, R. C., Granier, S., Gmeiner, P., Husbands, S. M., Traynor, J. R., Weis, W. I., Steyaert, J., Dror, R. O., and Kobilka, B. K. (2015) Structural Insights into M-Opioid Receptor Activation. Nature 524 (7565), 315– 321,  DOI: 10.1038/nature14886
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    Structural insights into μ-opioid receptor activation
    Huang, Weijiao; Manglik, Aashish; Venkatakrishnan, A. J.; Laeremans, Toon; Feinberg, Evan N.; Sanborn, Adrian L.; Kato, Hideaki E.; Livingston, Kathryn E.; Thorsen, Thor S.; Kling, Ralf C.; Granier, Sebastien; Gmeiner, Peter; Husbands, Stephen M.; Traynor, John R.; Weis, William I.; Steyaert, Jan; Dror, Ron O.; Kobilka, Brian K.
    Nature (London, United Kingdom) (2015), 524 (7565), 315-321CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
    Activation of the μ-opioid receptor (μOR) is responsible for the efficacy of the most effective analgesics. To shed light on the structural basis for μOR activation, here we report a 2.1 Å X-ray crystal structure of the murine μOR bound to the morphinan agonist BU72 and a G protein mimetic camelid antibody fragment Nb39 (nanobody 39). The BU72-stabilized changes in the μOR binding pocket are subtle and differ from those obsd. for agonist-bound structures of the β2-adrenergic receptor (β2AR) and the M2 muscarinic receptor (M2R). Comparison with active β2AR reveals a common rearrangement in the packing of three conserved amino acids in the core of the μOR, and mol. dynamics simulations illustrate how the ligand-binding pocket is conformationally linked to this conserved triad. Addnl., an extensive polar network between the ligand-binding pocket and the cytoplasmic domains appears to play a similar role in signal propagation for all three G-protein-coupled receptors.
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    Che, T., Majumdar, S., Zaidi, S. A., Ondachi, P., McCorvy, J. D., Wang, S., Mosier, P. D., Uprety, R., Vardy, E., Krumm, B. E., Han, G. W., Lee, M.-Y., Pardon, E., Steyaert, J., Huang, X.-P., Strachan, R. T., Tribo, A. R., Pasternak, G. W., Carroll, F. I., Stevens, R. C., Cherezov, V., Katritch, V., Wacker, D., and Roth, B. L. (2018) Structure of the Nanobody-Stabilized Active State of the Kappa Opioid Receptor. Cell 172 (1), 55– 67, e15.  DOI: 10.1016/j.cell.2017.12.011
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    Structure of the nanobody-stabilized active state of the Kappa opioid receptor
    Che, Tao; Majumdar, Susruta; Zaidi, Saheem A.; Ondachi, Pauline; McCorvy, John D.; Wang, Sheng; Mosier, Philip D.; Uprety, Rajendra; Vardy, Eyal; Krumm, Brian E.; Han, Gye Won; Lee, Ming-Yue; Pardon, Els; Steyaert, Jan; Huang, Xi-Ping; Strachan, Ryan T.; Tribo, Alexandra R.; Pasternak, Gavril W.; Carroll, F. Ivy; Stevens, Raymond C.; Cherezov, Vadim; Katritch, Vsevolod; Wacker, Daniel; Roth, Bryan L.
    Cell (Cambridge, MA, United States) (2018), 172 (1-2), 55-67.e15CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
    The κ-opioid receptor (KOP) mediates the actions of opioids with hallucinogenic, dysphoric, and analgesic activities. The design of KOP analgesics devoid of hallucinatory and dysphoric effects has been hindered by an incomplete structural and mechanistic understanding of KOP agonist actions. Here, we provide a crystal structure of human KOP in complex with the potent epoxymorphinan opioid agonist MP1104 and an active-state-stabilizing nanobody. Comparisons between inactive- and active-state opioid receptor structures reveal substantial conformational changes in the binding pocket and intracellular and extracellular regions. Extensive structural anal. and exptl. validation illuminate key residues that propagate larger-scale structural rearrangements and transducer binding that, collectively, elucidate the structural determinants of KOP pharmacol., function, and biased signaling. These mol. insights promise to accelerate the structure-guided design of safer and more effective κ-opioid receptor therapeutics.
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    Wacker, D., Wang, S., McCorvy, J. D., Betz, R. M., Venkatakrishnan, A. J., Levit, A., Lansu, K., Schools, Z. L., Che, T., Nichols, D. E., Shoichet, B. K., Dror, R. O., and Roth, B. L. (2017) Crystal Structure of an LSD-Bound Human Serotonin Receptor. Cell 168 (3), 377– 389, e12.  DOI: 10.1016/j.cell.2016.12.033
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    Crystal structure of an LSD-bound human serotonin receptor
    Wacker, Daniel; Wang, Sheng; McCorvy, John D.; Betz, Robin M.; Venkatakrishnan, A. J.; Levit, Anat; Lansu, Katherine; Schools, Zachary L.; Che, Tao; Nichols, David E.; Shoichet, Brian K.; Dror, Ron O.; Roth, Bryan L.
    Cell (Cambridge, MA, United States) (2017), 168 (3), 377-389.e12CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
    The prototypical hallucinogen, LSD, acts via serotonin receptors, and here the authors describe the crystal structure of LSD in complex with human serotonin receptor 5-HT2B. The complex revealed conformational rearrangements to accommodate LSD, providing a structural explanation for the conformational selectivity of LSD's key diethylamide moiety. LSD dissocd. exceptionally slow from both 5-HT2BR and 5-HT2AR, a major target for its psychoactivity. Mol. dynamics (MD) simulations suggested that LSD's slow binding kinetics may be due to a "lid" formed by extracellular loop 2 (EL2) at the entrance to the binding pocket. A mutation predicted to increase the mobility of this lid greatly accelerated LSD's binding kinetics and selectively dampened LSD-mediated β-arrestin 2 recruitment. Thus, this study reveals an unexpected binding mode of LSD, illuminates key features of its kinetics, stereochem., and signaling, and provides a mol. explanation for LSD's actions at human serotonin receptors.
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    Fiser, A. and Sali, A. (2003) ModLoop: Automated Modeling of Loops in Protein Structures. Bioinformatics 19 (18), 2500– 2501,  DOI: 10.1093/bioinformatics/btg362
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    ModLoop: automated modeling of loops in protein structures
    Fiser, Andras; Sali, Andrej
    Bioinformatics (2003), 19 (18), 2500-2501CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
    Summary: ModLoop is a web server for automated modeling of loops in protein structures. The input is the at. coordinates of the protein structure in the Protein Data Bank format, and the specification of the starting and ending residues of one or more segments to be modeled, contg. no more than 20 residues in total. The output is the coordinates of the non-hydrogen atoms in the modeled segments. A user provides the input to the server via a simple web interface, and receives the output by e-mail. The server relies on the loop modeling routine in MODELLER that predicts the loop conformations by satisfaction of spatial restraints, without relying on a database of known protein structures. For a rapid response, ModLoop runs on a cluster of Linux PC computers.
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    Jo, S., Kim, T., Iyer, V. G., and Im, W. (2008) CHARMM-GUI: A Web-Based Graphical User Interface for CHARMM. J. Comput. Chem. 29 (11), 1859– 1865,  DOI: 10.1002/jcc.20945
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    CHARMM-GUI: a web-based graphical user interface for CHARMM
    Jo, Sunhwan; Kim, Taehoon; Iyer, Vidyashankara G.; Im, Wonpil
    Journal of Computational Chemistry (2008), 29 (11), 1859-1865CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
    CHARMM is an academic research program used widely for macromol. mechanics and dynamics with versatile anal. and manipulation tools of at. coordinates and dynamics trajectories. CHARMM-GUI, http://www.charmm-gui.org, has been developed to provide a web-based graphical user interface to generate various input files and mol. systems to facilitate and standardize the usage of common and advanced simulation techniques in CHARMM. The web environment provides an ideal platform to build and validate a mol. model system in an interactive fashion such that, if a problem is found through visual inspection, one can go back to the previous setup and regenerate the whole system again. In this article, we describe the currently available functional modules of CHARMM-GUI Input Generator that form a basis for the advanced simulation techniques. Future directions of the CHARMM-GUI development project are also discussed briefly together with other features in the CHARMM-GUI website, such as Archive and Movie Gallery.
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    Trott, O. and Olson, A. J. (2010) AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading. J. Comput. Chem. 31 (2), 455– 461,  DOI: 10.1002/jcc.21334
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    AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
    Trott, Oleg; Olson, Arthur J.
    Journal of Computational Chemistry (2010), 31 (2), 455-461CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
    AutoDock Vina, a new program for mol. docking and virtual screening, is presented. AutoDock Vina achieves an approx. 2 orders of magnitude speed-up compared with the mol. docking software previously developed in the authors' lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by the authors' tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calcs. the grid maps and clusters the results in a way transparent to the user.
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    Phillips, J. C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., Chipot, C., Skeel, R. D., Kalé, L., and Schulten, K. (2005) Scalable Molecular Dynamics with NAMD. J. Comput. Chem. 26 (16), 1781– 1802,  DOI: 10.1002/jcc.20289
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    Scalable molecular dynamics with NAMD
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    Journal of Computational Chemistry (2005), 26 (16), 1781-1802CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
    NAMD is a parallel mol. dynamics code designed for high-performance simulation of large biomol. systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical mol. dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temp. and pressure controls used. Features for steering the simulation across barriers and for calcg. both alchem. and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomol. system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the mol. graphics/sequence anal. software VMD and the grid computing/collab. software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu.
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    Lenselink, E. B., Louvel, J., Forti, A. F., van Veldhoven, J. P. D., de Vries, H., Mulder-Krieger, T., McRobb, F. M., Negri, A., Goose, J., Abel, R., van Vlijmen, H. W. T., Wang, L., Harder, E., Sherman, W., Ijzerman, A. P., and Beuming, T. (2016) Predicting Binding Affinities for GPCR Ligands Using Free-Energy Perturbation. ACS Omega 1 (2), 293– 304,  DOI: 10.1021/acsomega.6b00086
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    Predicting Binding Affinities for GPCR Ligands Using Free-Energy Perturbation
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    ACS Omega (2016), 1 (2), 293-304CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)
    The rapid growth of structural information for G-protein-coupled receptors (GPCRs) has led to a greater understanding of their structure, function, selectivity, and ligand binding. Although novel ligands have been identified using methods such as virtual screening, computationally driven lead optimization has been possible only in isolated cases because of challenges assocd. with predicting binding free energies for related compds. Here, the authors provide a systematic characterization of the performance of free-energy perturbation (FEP) calcns. to predict relative binding free energies of congeneric ligands binding to GPCR targets using a consistent protocol and no adjustable parameters. Using the FEP+ package, first the authors validated the protocol, which includes a full lipid bilayer and explicit solvent, by predicting the binding affinity for a total of 45 different ligands across four different GPCRs (adenosine A2AAR, β1 adrenergic, CXCR4 chemokine, and δ opioid receptors). Comparison with exptl. binding affinity measurements revealed a highly predictive ranking correlation (av. spearman ρ = 0.55) and low root-mean-square error (0.80 kcal/mol). Next, the authors applied FEP+ in a prospective project, where the authors predicted the affinity of novel, potent adenosine A2A receptor (A2AR) antagonists. Four novel compds. were synthesized and tested in a radioligand displacement assay, yielding affinity values in the nanomolar range. The affinity of two out of the four novel ligands (plus three previously reported compds.) was correctly predicted (within 1 kcal/mol), including one compd. with approx. a 10-fold increase in affinity compared to the starting compd. Detailed analyses of the simulations underlying the predictions provided insights into the structural basis for the two cases where the affinity was overpredicted. Taken together, these results establish a protocol for systematically applying FEP+ to GPCRs and provide guidelines for identifying potent mols. in drug discovery lead optimization projects.
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    Absolute binding free energy calculations using molecular dynamics simulations with restraining potentials
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    Biophysical Journal (2006), 91 (8), 2798-2814CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)
    The abs. (std.) binding free energy of eight FK506-related ligands to FKBP12 is calcd. using free energy perturbation mol. dynamics (FEP/MD) simulations with explicit solvent. A no. of features are implemented to improve the accuracy and enhance the convergence of the calcns. First, the abs. binding free energy is decompd. into sequential steps during which the ligand-surrounding interactions as well as various biasing potentials restraining the translation, orientation, and conformation of the ligand are turned "on" and "off.". Second, sampling of the ligand conformation is enforced by a restraining potential based on the root mean-square deviation relative to the bound state conformation. The effect of all the restraining potentials is rigorously unbiased, and it is shown explicitly that the final results are independent of all artificial restraints. Third, the repulsive and dispersive free energy contribution arising from the Lennard-Jones interactions of the ligand with its surrounding (protein and solvent) is calcd. using the Weeks-Chandler-Andersen sepn. This sepn. also improves convergence of the FEP/MD calcns. Fourth, to decrease the computational cost, only a small no. of atoms in the vicinity of the binding site are simulated explicitly, while all the influence of the remaining atoms is incorporated implicitly using the generalized solvent boundary potential (GSBP) method. With GSBP, the size of the simulated FKBP12/ligand systems is significantly reduced, from ∼25,000 to 2500. The computations are very efficient and the statistical error is small (∼1 kcal/mol). The calcd. binding free energies are generally in good agreement with available exptl. data and previous calcns. (within ∼2 kcal/mol). The present results indicate that a strategy based on FEP/MD simulations of a reduced GSBP at. model sampled with conformational, translational, and orientational restraining potentials can be computationally inexpensive and accurate.
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    Deflorian, F., Perez-Benito, L., Lenselink, E. B., Congreve, M., van Vlijmen, H. W. T., Mason, J. S., Graaf de, C., and Tresadern, G. (2020) Accurate Prediction of GPCR Ligand Binding Affinity with Free Energy Perturbation. J. Chem. Inf. Model. 60 (11), 5563– 5579,  DOI: 10.1021/acs.jcim.0c00449
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    Accurate Prediction of GPCR Ligand Binding Affinity with Free Energy Perturbation
    Deflorian, Francesca; Perez-Benito, Laura; Lenselink, Eelke B.; Congreve, Miles; van Vlijmen, Herman W. T.; Mason, Jonathan S.; Graaf, Chris de; Tresadern, Gary
    Journal of Chemical Information and Modeling (2020), 60 (11), 5563-5579CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
    The computational prediction of relative binding free energies is a crucial goal for drug discovery, and G protein-coupled receptors (GPCRs) are arguably the most important drug target class. However, they present increased complexity to model compared to sol. globular proteins. Despite breakthroughs, exptl. X-ray crystal and cryo-EM structures are challenging to attain, meaning computational models of the receptor and ligand binding mode are sometimes necessary. This leads to uncertainty in understanding ligand-protein binding induced changes such as, water positioning and displacement, side chain positioning, hydrogen bond networks, and the overall structure of the hydration shell around the ligand and protein. In other words, the very elements that define structure activity relationships (SARs) and are crucial for accurate binding free energy calcns. are typically more uncertain for GPCRs. In this work we use free energy perturbation (FEP) to predict the relative binding free energies for ligands of two different GPCRs. We pinpoint the key aspects for success such as the important role of key water mols., amino acid ionization states, and the benefit of equilibration with specific ligands. Initial calcns. following typical FEP setup and execution protocols delivered no correlation with expt., but we show how results are improved in a logical and systematic way. This approach gave, in the best cases, a coeff. of detn. (R2) compared with expt. in the range of 0.6-0.9 and mean unsigned errors compared to expt. of 0.6-0.7 kcal/mol. We anticipate that our findings will be applicable to other difficult-to-model protein ligand data sets and be of wide interest for the community to continue improving FE binding energy predictions.
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    The theory of receptor-ligand binding equil. has long been well-established in biochem., and was primarily constructed to describe dil. aq. solns. Accordingly, few computational approaches have been developed for making quant. predictions of binding probabilities in environments other than dil. isotropic soln. Existing techniques, ranging from simple automated docking procedures to sophisticated thermodn.-based methods, have been developed with sol. proteins in mind. Biol. and pharmacol. relevant protein-ligand interactions often occur in complex environments, including lamellar phases like membranes and crowded, nondilute solns. Here, the authors revisit the theor. bases of ligand binding equil., avoiding overly specific assumptions that are nearly always made when describing receptor-ligand binding. Building on this formalism, the authors extend the asymptotically exact Alchem. Free Energy Perturbation technique to quantifying occupancies of sites on proteins in a complex bulk, including phase-sepd., anisotropic, or nondilute solns., using a thermodynamically consistent and easily generalized approach that resolves several ambiguities of current frameworks. To incorporate the complex bulk without overcomplicating the overall thermodn. cycle, the authors simplify the common approach for ligand restraints by using a single distance-from-bound-configuration (DBC) ligand restraint during AFEP decoupling from protein. DBC restraints should be generalizable to binding modes of most small mols., even those with strong orientational dependence. The authors apply this approach to compute the likelihood that membrane cholesterol binds to known crystallog. sites on three GPCRs (β2-adrenergic, 5HT-2B, and μ-opioid) at a range of concns. Nonideality of cholesterol in a binary cholesterol:phosphatidylcholine (POPC) bilayer is characterized and consistently incorporated into the interpretation. The authors find that the three sites exhibit very different affinities for cholesterol: The site on the adrenergic receptor is predicted to be high affinity, with 50% occupancy for 1:109 CHOL:POPC mixts. The sites on the 5HT-2B and μ-opioid receptor are predicted to be lower affinity, with 50% occupancy for 1:103 CHOL:POPC and 1:102 CHOL:POPC, resp. These results could not have been predicted from the crystal structures alone.
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    A review. Free energy simulations for electrostatic and charging processes in complex mol. systems encounter specific difficulties owing to the long-range, 1/r Coulomb interaction. To calc. the solvation free energy of a simple ion, it is essential to take into account the polarization of nearby solvent but also the electrostatic potential drop across the liq.-gas boundary, however distant. The latter does not exist in a simulation model based on periodic boundary conditions because there is no phys. boundary to the system. An important consequence is that the ref. value of the electrostatic potential is not an ion in a vacuum. Also, in an infinite system, the electrostatic potential felt by a perturbing charge is conditionally convergent and dependent on the choice of computational conventions. Furthermore, with Ewald lattice summation and tinfoil conducting boundary conditions, the charges experience a spurious shift in the potential that depends on the details of the simulation system such as the vol. fraction occupied by the solvent. All these issues can be handled with established computational protocols, as reviewed here and illustrated for several small ions and three solvated proteins.
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    Electrostatic free energies play an essential role in numerous biomol. processes occurring in soln. Difficulties arise when the long-range Coulomb interaction is computed for idealised infinite simulation models with periodic boundary conditions. To maintain a neutral simulation box and a finite per-box energy, a neutralising charge d. or 'gellium' is commonly used, leading to a mean box potential that is constrained to be rigorously equal to zero at all times. Thus, in considering quantities such as ion solvation free energy, the potential drop to move from solvent into the usual, gas phase ref. state is missing. In fact, for an infinite mol. system, the electrostatic potential itself is not uniquely defined, but takes the form of an infinite series that is only conditionally convergent. This leads to several possible computational conventions that give different values for the potential and field, all math. valid. For exptl. measurable quantities, however, unique results are obtained when sufficiently large simulation boxes are utilized. These concepts are detailed, as well as a fundamental, linear response theor. framework that provides qual. understanding of the phys. processes involved, esp. dielec. relaxation of the environment in response to a new solute charge. Illustrative applications to ligand binding and biomol. electron transfer are described.
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    Free Energy of Ionic Hydration
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    The hydration free energies of ions exhibit an approx. quadratic dependence on the ionic charge, as predicted by the Born model. The authors analyze this behavior using second-order perturbation theory. This provides effective methods for calcg. free energies from equil. computer simulations. The av. and the fluctuation of the electrostatic potential at charge sites appear as the first coeffs. in a Taylor expansion of the free energy of charging. Combining the data from different charge states (e.g., charged and uncharged) allows calcn. of free-energy profiles as a function of the ionic charge. The first two Taylor coeffs. of the free-energy profiles can be computed accurately from equil. simulations, but they are affected by a strong system-size dependence. The authors apply corrections for these finite-size effects by using Ewald lattice summation and adding the self-interactions consistently. An analogous procedure is used for the reaction-field electrostatics. Results are presented for a model ion with methane-like Lennard-Jones parameters in simple point charge water. Two very closely quadratic regimes are found with different parameters for pos. and neg. ions. The hydration free energy of potassium, calcium, fluoride, chloride, and bromide ions are studied. The neg. ions are solvated more strongly (as measured by hydration free energies) compared to pos. ions of equal size, in agreement with exptl. data. The authors ascribe this preference of neg. ions to their strong interactions with water hydrogens, which can penetrate the ionic van der Waals shell without direct energetic penalty in the models used. In addn., they consistently find a pos. electrostatic potential at the center of uncharged Lennard-Jones particles in water, which also favors neg. ions. Regarding the effects of a finite system size, they show that even using only 16 water mols. it is possible to calc. accurately the hydration free energy of sodium, if self-interactions are considered.

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  • Abstract

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    Figure 1

    Figure 1. (a) Key residue interactions of protonated HNK in MOR and KOR. In each case, the ligand is in the orthosteric binding pocket. Note the presence of D3.32 (with hydrogen bond) and H6.52. See Supporting Table 2 for comprehensive list of nearby residues. (b) Root mean square deviation (RMSD) of ligand over simulation time in equilibrium MD simulations prior to FEP, for HNK. Plots for all ligands as well as receptor pocket available in the Supporting Information. (c) ΔG vs lambda plots of ligand–protein decoupling FEP simulations for HNK, both neutral (left) and protonated (right), illustrating the smoothness of these curves, which are representative of all FEP simulations. Calculations for MOR and KOR as well as both binding pocket His protonation states are shown. Forward and backward legs of these interleaved double-wide sampled simulations are shown. More detailed plots, where each curve is labeled, are available in the Supporting Information.

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    Figure 2

    Figure 2. Bar plots of binding affinities of ketamine and metabolites with opioid receptors. These figures include the cost of desolvation from aqueous solution and binding to the receptor.

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    Figure 3

    Figure 3. Sigmoidal dose–response inhibition curves from [35S]GTPγS assays, including standard deviations. Increasing concentrations of HNK depress activation in both MOR and KOR, suggesting an inverse agonist effect. This is attenuated by pretreatment with naltrexone in both MOR and KOR.

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  • References

    This article references 60 other publications.

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      Williams, N. R., Heifets, B. D., Blasey, C., Sudheimer, K., Pannu, J., Pankow, H., Hawkins, J., Birnbaum, J., Lyons, D. M., Rodriguez, C. I., and Schatzberg, A. F. (2018) Attenuation of Antidepressant Effects of Ketamine by Opioid Receptor Antagonism. Am. J. Psychiatry 175, 1205,  DOI: 10.1176/appi.ajp.2018.18020138
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      OBJECTIVE: In addition to N-methyl-d-aspartate receptor antagonism, ketamine produces opioid system activation. The objective of this study was to determine whether opioid receptor antagonism prior to administration of intravenous ketamine attenuates its acute antidepressant or dissociative effects. METHOD: In a proposed double-blind crossover study of 30 adults with treatment-resistant depression, the authors performed a planned interim analysis after studying 14 participants, 12 of whom completed both conditions in randomized order: placebo or 50 mg of naltrexone preceding intravenous infusion of 0.5 mg/kg of ketamine. Response was defined as a reduction ≥50% in score on the 17-item Hamilton Depression Rating Scale (HAM-D) score on postinfusion day 1. RESULTS: In the interim analysis, seven of 12 adults with treatment-resistant depression met the response criterion during the ketamine plus placebo condition. Reductions in 6-item and 17-item HAM-D scores among participants in the ketamine plus naltrexone condition were significantly lower than those of participants in the ketamine plus placebo condition on postinfusion days 1 and 3. Secondary analysis of all participants who completed the placebo and naltrexone conditions, regardless of the robustness of response to ketamine, showed similar results. There were no differences in ketamine-induced dissociation between conditions. Because naltrexone dramatically blocked the antidepressant but not the dissociative effects of ketamine, the trial was halted at the interim analysis. CONCLUSIONS: The findings suggest that ketamine's acute antidepressant effect requires opioid system activation. The dissociative effects of ketamine are not mediated by the opioid system, and they do not appear sufficient without the opioid effect to produce the acute antidepressant effects of ketamine in adults with treatment-resistant depression.
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      Klein, M. E., Chandra, J., Sheriff, S., and Malinow, R. (2020) Opioid System Is Necessary but Not Sufficient for Antidepressive Actions of Ketamine in Rodents. Proc. Natl. Acad. Sci. U. S. A. 117 (5), 2656– 2662,  DOI: 10.1073/pnas.1916570117
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      Opioid system is necessary but not sufficient for antidepressive actions of ketamine in rodents
      Klein, Matthew E.; Chandra, Joshua; Sheriff, Salma; Malinow, Roberto
      Proceedings of the National Academy of Sciences of the United States of America (2020), 117 (5), 2656-2662CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      Slow response to the std. treatment for depression increases suffering and risk of suicide. Ketamine, an N-methyl-d-aspartate (NMDA) receptor antagonist, can rapidly alleviate depressive symptoms and reduce suicidality, possibly by decreasing hyperactivity in the lateral habenula (LHb) brain nucleus. Here we find that in a rat model of human depression, opioid antagonists abolish the ability of ketamine to reduce the depression-like behavioral and LHb hyperactive cellular phenotypes. However, activation of opiate receptors alone is not sufficient to produce ketamine-like effects, nor does ketamine mimic the hedonic effects of an opiate, indicating that the opioid system does not mediate the actions of ketamine but rather is permissive. Thus, ketamine does not act as an opiate but its effects require both NMDA and opiate receptor signaling, suggesting that interactions between these two neurotransmitter systems are necessary to achieve an antidepressant effect.
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      Ion, B. F., Wells, M. M., Chen, Q., Xu, Y., and Tang, P. (2017) Ketamine Inhibition of the Pentameric Ligand-Gated Ion Channel GLIC. Biophys. J. 113 (3), 605– 612,  DOI: 10.1016/j.bpj.2017.06.041
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      Ketamine Inhibition of the Pentameric Ligand-Gated Ion Channel GLIC
      Ion, Bogdan F.; Wells, Marta M.; Chen, Qiang; Xu, Yan; Tang, Pei
      Biophysical Journal (2017), 113 (3), 605-612CODEN: BIOJAU; ISSN:0006-3495. (Cell Press)
      Ketamine inhibits pentameric ligand-gated ion channels (pLGICs), including the bacterial pLGIC from Gloeobacter violaceus (GLIC). The crystal structure of GLIC shows R-ketamine bound to an extracellular intersubunit cavity. Here, we performed mol. dynamics simulations of GLIC in the absence and presence of R- or S-ketamine. No stable binding of S-ketamine in the original cavity was obsd. in the simulations, largely due to its unfavorable access to residue D154, which provides important electrostatic interactions to stabilize R-ketamine binding. Contrary to the sym. binding shown in the crystal structure, R-ketamine moved away from some of the binding sites and was bound to GLIC asym. at the end of simulations. The asym. binding is consistent with the exptl. measured neg. cooperativity of ketamine binding to GLIC. In the presence of R-ketamine, all subunits showed changes in structure and dynamics, irresp. of binding stability; the extracellular intersubunit cavity expanded and intersubunit electrostatic interactions involved in channel activation were altered. R-ketamine binding promoted a conformational shift toward closed GLIC. Conformational changes near the ketamine-binding site were propagated to the interface between the extracellular and transmembrane domains, and further to the pore-lining TM2 through two pathways: pre-TM1 and the β1-β2 loop. Both signaling pathways have been predicted previously using the perturbation-based Markovian transmission model. The study provides a structural and dynamics basis for the inhibitory modulation of ketamine on pLGICs.
    4. 4
      Pan, J., Chen, Q., Willenbring, D., Mowrey, D., Kong, X.-P., Cohen, A., Divito, C. B., Xu, Y., and Tang, P. (2012) Structure of the Pentameric Ligand-Gated Ion Channel GLIC Bound with Anesthetic Ketamine. Struct. London Engl. 1993 20 (9), 1463– 1469,  DOI: 10.1016/j.str.2012.08.009
      4
      Structure of the pentameric ligand-gated ion channel GLIC bound with anesthetic ketamine
      Pan Jianjun; Chen Qiang; Willenbring Dan; Mowrey David; Kong Xiang-Peng; Cohen Aina; Divito Christopher B; Xu Yan; Tang Pei
      Structure (London, England : 1993) (2012), 20 (9), 1463-9 ISSN:.
      Pentameric ligand-gated ion channels (pLGICs) are targets of general anesthetics, but a structural understanding of anesthetic action on pLGICs remains elusive. GLIC, a prokaryotic pLGIC, can be inhibited by anesthetics, including ketamine. The ketamine concentration leading to half-maximal inhibition of GLIC (58 μM) is comparable to that on neuronal nicotinic acetylcholine receptors. A 2.99 ÅA resolution X-ray structure of GLIC bound with ketamine revealed ketamine binding to an intersubunit cavity that partially overlaps with the homologous antagonist-binding site in pLGICs. The functional relevance of the identified ketamine site was highlighted by profound changes in GLIC activation upon cysteine substitution of the cavity-lining residue N152. The relevance is also evidenced by changes in ketamine inhibition upon the subsequent chemical labeling of N152C. The results provide structural insight into the molecular recognition of ketamine and are valuable for understanding the actions of anesthetics and other allosteric modulators on pLGICs.
    5. 5
      Bevan, R. K., Rose, M. A., and Duggan, K. A. (1997) Evidence for Direct Interaction of Ketamine with Alpha 1- and Beta 2-Adrenoceptors. Clin. Exp. Pharmacol. Physiol. 24 (12), 923– 926,  DOI: 10.1111/j.1440-1681.1997.tb02720.x
      5
      Evidence for direct interaction of ketamine with alpha 1- and beta 2-adrenoceptors
      Bevan R K; Rose M A; Duggan K A
      Clinical and experimental pharmacology & physiology (1997), 24 (12), 923-6 ISSN:0305-1870.
      1. Ketamine has a number of effects that suggest that it may interact with alpha- and beta-adrenoceptors. To date, the experimental evidence for this has been indirect and has been based on physiological studies using competitive blocking agents. In the present study we sought to determine from receptor binding studies whether ketamine binds directly to alpha- and beta-adrenoceptors. 2. Membrane preparations of alpha 1- and beta 2-adrenergic binding sites were obtained from urinary bladder and urethrae of sheep. These binding sites were characterized by saturation analyses using [3H]-prazosin for alpha 1-adrenoceptor binding sites and [125I]-cyanopindolol (CYP) for the beta 2-adrenoceptor binding sites. The receptors were further characterized by displacement studies using selective and non-selective antagonists. 3. Studies in which ketamine was used to displace [3H]-prazosin revealed a Kd of 3.40 +/- 1.23 x 10(-3) mol/L for ketamine binding to alpha 1-adrenoceptors. Displacement studies of [125I]-CYP by ketamine showed a Kd of 0.35 +/- 0.03 x 10(-3) mol/L for ketamine binding to beta 2-adrenoceptors. 4. We conclude that ketamine interacts directly with both alpha 1- and beta 2-adrenoceptors and that such interactions probably explain the reported effects of this agent on the vasculature and the bronchial tree.
    6. 6
      Gupta, A., Devi, L. A., and Gomes, I. (2011) Potentiation of μ-Opioid Receptor-Mediated Signaling by Ketamine: Opioid-Ketamine Interactions. J. Neurochem. 119 (2), 294– 302,  DOI: 10.1111/j.1471-4159.2011.07361.x
      6
      Potentiation of μ-opioid receptor-mediated signaling by ketamine
      Gupta, Achla; Devi, Lakshmi A.; Gomes, Ivone
      Journal of Neurochemistry (2011), 119 (1 & 2), 294-302CODEN: JONRA9; ISSN:0022-3042. (Wiley-Blackwell)
      Ketamine, a clin. relevant drug, has been shown to enhance opioid-induced analgesia and prevent hyperalgesia. However, the mol. mechanisms involved are not clearly understood. As previous studies found that activation of opioid receptors leads to the phosphorylation of mitogen-activated protein kinases, we investigated whether ketamine could modulate μ-opioid receptor (μOR)-mediated ERK1/2 phosphorylation. We find that acute treatment with ketamine enhances (∼2- to 3-fold) the levels of opioid-induced ERK1/2 phosphorylation in recombinant as well as cells endogenously expressing μOR. Interestingly, we find that in the absence of ketamine ERK1/2 signaling is desensitized 10 min after opioid exposure whereas in its presence significant levels (∼3-fold over basal) are detected. In addn., ketamine increases the rate of resensitization of opioid-mediated ERK1/2 signaling (15 min in its presence vs. 30 min in its absence). These results suggest that ketamine increases the effectiveness of opiate-induced signaling by affecting multiple mechanisms. In addn., these effects are obsd. in heterologous cells expressing μOR suggesting a non-NMDA receptor-mediated action of ketamine. Together this could, in part, account for the obsd. effects of ketamine on the enhancement of the analgesic effects of opiates as well as in the duration of opiate-induced analgesia.
    7. 7
      Hirota, K., Okawa, H., Appadu, B. L., Grandy, D. K., Devi, L. A., and Lambert, D. G. (1999) Stereoselective Interaction of Ketamine with Recombinant Mu, Kappa, and Delta Opioid Receptors Expressed in Chinese Hamster Ovary Cells. Anesthesiology 90 (1), 174– 182,  DOI: 10.1097/00000542-199901000-00023
      7
      Stereoselective interaction of ketamine with recombinant μ, κ, and δ opioid receptors expressed in Chinese hamster ovary cells
      Hirota, Kazuyoshi; Okawa, Hirobumi; Appadu, Balraj L.; Grandy, David K.; Devi, Lakshmi A.; Lambert, David G.
      Anesthesiology (1999), 90 (1), 174-182CODEN: ANESAV; ISSN:0003-3022. (Lippincott Williams & Wilkins)
      Background: The authors examd. the interaction of ketamine with recombinant μ, κ, and δ opioid receptors and recombinant orphan opioid receptors expressed in Chinese hamster ovary cells (CHO-μ, CHO-κ, CHO-δ, and CHOORL1, resp.). Methods: CHO-μ, CHO-κ, and CHO-δ membranes were incubated with the opioid receptor radioligand [3H]diprenorphine at room temp. Ketamine (racemic, R(-) and S(+)) was included at concns. covering the clin. range. CHOORL1 membranes were incubated with [125I]Tyr14nociceptin and racemic ketamine at room temp. The effects of racemic ketamine and selective opioid receptor agonists (μ: [D-Ala2, MePhe4, Gly(ol)5] enkephalin (DAMGO); κ: spiradoline or δ: [D-pen2, D-pen5] enkephalin (DPDPE)) on forskolin-stimulated cAMP formation also were examd. Data are mean ± SEM. Results: Racemic ketamine increased the radioligand equil. dissocn. const. for [3H]diprenorphine from 85±5 to 273±11, 91±6 to 154±16, and 372±15 to 855±42 pM in CHO-μ, CHO-κ, and CHO-δ, resp. The concn. of radioligand bound at satn. was unaffected. In CHO-μ and CHO-κ cells, racemic ketamine did not slow the rate of naloxone-induced [3H]diprenorphine dissocn. Ketamine and its isomers also displaced [3H]diprenorphine binding to μ, κ, and δ receptors in a dose-dependent manner, with pKi values for racemic ketamine of 4.38±0.02, 4.55±0.04, and 3.57±0.02, resp. S(+)-ketamine was two to three times more potent than R(-)-ketamine at μ and κ receptors. Racemic ketamine displaced [125I]Tyr14nociceptin with an estd. affinity const. of 0.5 mM. Racemic ketamine inhibited the formation of cAMP (naloxone insensitive) in a dose-dependent manner (concn. producing 50% inhibition ∼ 2 mM) in all cell lines, including untransfected CHO cells. Ketamine (100 μM) reversed DAMGO (μ) and spiradoline (κ) inhibition of formation of cAMP. Conclusions: Ketamine interacts stereoselectively with recombinant μ and κ opioid receptors.
    8. 8
      Ho, J., Perez-Aguilar, J. M., Gao, L., Saven, J. G., Matsunami, H., and Eckenhoff, R. G. (2015) Molecular Recognition of Ketamine by a Subset of Olfactory G Protein-Coupled Receptors. Sci. Signal 8 (370), ra33-ra33  DOI: 10.1126/scisignal.2005912
      There is no corresponding record for this reference.
    9. 9
      Smith, D. J., Bouchal, R. L., deSanctis, C. A., Monroe, P. J., Amedro, J. B., Perrotti, J. M., and Crisp, T. (1987) Properties of the Interaction between Ketamine and Opiate Binding Sites in Vivo and in Vitro. Neuropharmacology 26 (9), 1253– 1260,  DOI: 10.1016/0028-3908(87)90084-0
      9
      Properties of the interaction between ketamine and opiate binding sites in vivo and in vitro
      Smith, D. J.; Bouchal, R. L.; DeSanctis, C. A.; Monroe, P. J.; Amedro, J. B.; Perrotti, J. M.; Crisp, T.
      Neuropharmacology (1987), 26 (9), 1253-60CODEN: NEPHBW; ISSN:0028-3908.
      The affinity and the specificity of ketamine were evaluated for binding sites labeled by prototypic μ, δ, κ, and σ-phencyclidine ligands. The concns. of ketamine achieved in the rat brain and spinal cord are adequate to interact at opiate receptor binding sites when analgesic doses are used. Morphine and ketamine may both show a preference for interaction at the μ-receptor in vitro, but the drugs have distinctly different characteristics of interaction at binding sites, distinguished by the prototype σ-phencyclidine radioligand, (±)-allylnormetazocine.
    10. 10
      Smith, D. J., Pekoe, G. M., Martin, L. L., and Coalgate, B. (1980) The Interaction of Ketamine with the Opiate Receptor. Life Sci. 26 (10), 789– 795,  DOI: 10.1016/0024-3205(80)90285-4
      10
      The interaction of ketamine with the opiate receptor
      Smith, David J.; Pekoe, Gary M.; Martin, Louis L.; Coalgate, Barbara
      Life Sciences (1980), 26 (10), 789-95CODEN: LIFSAK; ISSN:0024-3205.
      The analgesic effect of the anesthetic agent (±)-ketamine-HCl (I-HCl) [1867-66-9] was inhibited in rats by the narcotic receptor antagonist naloxone. Racemic I-HCl also displaced naloxone-3H in an opiate receptor binding assay. The potency of I in the assay was reduced nearly 6-fold by Na+, suggesting that the drug interacts as an agonist. However, some activity as an antagonist was not ruled out. The interaction of I with the opiate receptor was stereospecific, with the (+)-salt [33795-24-3] being more effective than the (-)-salt [33643-47-9]. The stereoselective nature of the interaction is consistent with other studies demonstrating that (+)-I-HCl has a greater analgesic effect than the (-)-I salt.
    11. 11
      Pacheco, D. d. F., Romero, T. R. L., and Duarte, I. D. G. (2014) Central Antinociception Induced by Ketamine Is Mediated by Endogenous Opioids and μ- and δ-Opioid Receptors. Brain Res. 1562, 69– 75,  DOI: 10.1016/j.brainres.2014.03.026
      11
      Central antinociception induced by ketamine is mediated by endogenous opioids and μ- and δ-opioid receptors
      Pacheco, Daniela da Fonseca; Romero, Thiago Roberto Lima; Duarte, Igor Dimitri Gama
      Brain Research (2014), 1562 (), 69-75CODEN: BRREAP; ISSN:0006-8993. (Elsevier B.V.)
      It is generally believed that NMDA receptor antagonism accounts for most of the anesthetic and analgesic effects of ketamine, however, it interacts at multiple sites in the central nervous system, including NMDA and non-NMDA glutamate receptors, nicotinic and muscarinic cholinergic receptors, and adrenergic and opioid receptors. Interestingly, it was shown that at supraspinal sites, ketamine interacts with the μ-opioid system and causes supraspinal antinociception. In this study, we investigated the involvement of endogenous opioids in ketamine-induced central antinociception. The nociceptive threshold for thermal stimulation was measured in Swiss mice using the tail-flick test. The drugs were administered via the intracerebroventricular route. Our results demonstrated that the opioid receptor antagonist naloxone, the μ-opioid receptor antagonist clocinnamox and the δ-opioid receptor antagonist naltrindole, but not the κ-opioid receptor antagonist nor-binaltorphimine, antagonized ketamine-induced central antinociception in a dose-dependent manner. Addnl., the administration of the aminopeptidase inhibitor bestatin significantly enhanced low-dose ketamine-induced central antinociception. These data provide evidence for the involvement of endogenous opioids and μ- and δ-opioid receptors in ketamine-induced central antinociception. In contrast, κ-opioid receptors not appear to be involved in this effect.
    12. 12
      Zhang, J., Li, S., and Hashimoto, K. (2014) R (−)-Ketamine Shows Greater Potency and Longer Lasting Antidepressant Effects than S (+)-Ketamine. Pharmacol., Biochem. Behav. 116, 137– 141,  DOI: 10.1016/j.pbb.2013.11.033
      12
      R (-)-ketamine shows greater potency and longer lasting antidepressant effects than S (+)-ketamine
      Zhang, Ji-chun; Li, Su-xia; Hashimoto, Kenji
      Pharmacology, Biochemistry and Behavior (2014), 116 (), 137-141CODEN: PBBHAU; ISSN:0091-3057. (Elsevier)
      The N-methyl-D-aspartate (NMDA) receptor antagonist ketamine is one of the most attractive antidepressants for treatment-resistant major depressive disorder (MDD). Ketamine (or RS (±)-ketamine) is a racemic mixt. contg. equal parts of R (-)-ketamine and S (+)-ketamine. In this study, we examd. the effects of R- and S-ketamine on depression-like behavior in juvenile mice after neonatal dexamethasone (DEX) exposure. In the tail suspension test (TST) and forced swimming test (FST), both isomers of ketamine significantly attenuated the increase in immobility time, seen in DEX-treated juvenile mice at 27 and 29 h resp., after ketamine injections. In the 1% sucrose preference test (SPT), both isomers significantly attenuated the reduced preference for 1% sucrose consumption in DEX-treated juvenile mice, 48 h after a ketamine injection. Interestingly, when immobility times were tested by the TST and FST at day 7, R-ketamine, but not S-ketamine, significantly lowered the increases in immobility seen in DEX-treated juvenile mice. This study shows that a single dose of R-ketamine produced rapid and long-lasting antidepressant effects in juvenile mice exposed neonatally to DEX. Therefore, R-ketamine appears to be a potent and safe antidepressant relative to S-ketamine, since R-ketamine may be free of psychotomimetic side effects.
    13. 13
      Zanos, P., Highland, J. N., Stewart, B. W., Georgiou, P., Jenne, C. E., Lovett, J., Morris, P. J., Thomas, C. J., Moaddel, R., Zarate, C. A., and Gould, T. D. (2019) (2R,6R)-Hydroxynorketamine Exerts MGlu2 Receptor-Dependent Antidepressant Actions. Proc. Natl. Acad. Sci. U. S. A. 116 (13), 6441– 6450,  DOI: 10.1073/pnas.1819540116
      13
      (2R,6R)-hydroxynorketamine exerts mGlu2 receptor-dependent antidepressant actions
      Zanos, Panos; Highland, Jaclyn N.; Stewart, Brent W.; Georgiou, Polymnia; Jenne, Carleigh E.; Lovett, Jacqueline; Morris, Patrick J.; Thomas, Craig J.; Moaddel, Ruin; Zarate, Carlos A. Jr.; Gould, Todd D.
      Proceedings of the National Academy of Sciences of the United States of America (2019), 116 (13), 6441-6450CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      Currently approved antidepressant drugs often take months to take full effect, and a$$Hat$$ 1/430% of depressed patients remain treatment resistant. In contrast, ketamine, when administered as a single subanesthetic dose, exerts rapid and sustained antidepressant actions. Preclin. studies indicate that the ketamine metabolite (2R,6R)-hydroxynorketamine [(2R,6R)-HNK] is a rapid-acting antidepressant drug candidate with limited dissocn. properties and abuse potential. We assessed the role of group II metabotropic glutamate receptor subtypes 2 (mGlu2) and 3 (mGlu3) in the antidepressant-relevant actions of (2R,6R)-HNK using behavioral, genetic, and pharmacol. approaches as well as cortical quant. EEG (qEEG) measurements in mice. Both ketamine and (2R,6R)-HNK prevented mGlu2/3 receptor agonist (LY379268)-induced body temp. increases in mice lacking the Grm3, but not Grm2, gene. This action was not replicated by NMDA receptor antagonists or a chem. variant of ketamine that limits metab. to (2R,6R)-HNK. The antidepressant-relevant behavioral effects and 30- to 80-Hz qEEG oscillation (gamma-range) increases resultant from (2R,6R)-HNK administration were prevented by pretreatment with an mGlu2/3 receptor agonist and absent in mice lacking the Grm2, but not Grm3a$$Hat$$ /a$$Hat$$ , gene. Combined subeffective doses of the mGlu2/3 receptor antagonist LY341495 and (2R,6R)-HNK exerted synergistic increases on gamma oscillations and antidepressant-relevant behavioral actions. These findings highlight that (2R,6R)-HNK exerts antidepressant-relevant actions via a mechanism converging with mGlu2 receptor signaling and suggest enhanced cortical gamma oscillations as a marker of target engagement relevant to antidepressant efficacy. Moreover, these results support the use of (2R,6R)-HNK and inhibitors of mGlu2 receptor function in clin. trials for treatment-resistant depression either alone or in combination.
    14. 14
      Fukumoto, K., Fogaça, M. V., Liu, R.-J., Duman, C., Kato, T., Li, X.-Y., and Duman, R. S. (2019) Activity-Dependent Brain-Derived Neurotrophic Factor Signaling Is Required for the Antidepressant Actions of (2R,6R)-Hydroxynorketamine. Proc. Natl. Acad. Sci. U. S. A. 116 (1), 297– 302,  DOI: 10.1073/pnas.1814709116
      14
      Activity-dependent brain-derived neurotrophic factor signaling is required for the antidepressant actions of (2R,6R)-hydroxynorketamine
      Fukumoto, Kenichi; Fogaca, Manoela V.; Liu, Rong-Jian; Duman, Catharine; Kato, Taro; Li, Xiao-Yuan; Duman, Ronald S.
      Proceedings of the National Academy of Sciences of the United States of America (2019), 116 (1), 297-302CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      Ketamine, a noncompetitive N-methyl-d-aspartate (NMDA) receptor antagonist, produces rapid and long-lasting antidepressant effects in major depressive disorder (MDD) patients. (2R,6R)-Hydroxynorketamine [(2R,6R)-HNK], a metabolite of ketamine, is reported to produce rapid antidepressant effects in rodent models without the side effects of ketamine. Importantly, (2R,6R)-HNK does not block NMDA receptors like ketamine, and the mol. signaling mechanisms for (2R,6R)-HNK remain unknown. Here, we examd. the involvement of BDNF/TrkB/mechanistic target of rapamycin complex 1 (mTORC1) signaling in the antidepressant actions of (2R,6R)-HNK. Intramedial prefrontal cortex (intra-mPFC) infusion or systemic (2R,6R)-HNK administration induces rapid and long-lasting antidepressant effects in behavioral tests, identifying the mPFC as a key region for the actions of (2R,6R)-HNK. The antidepressant actions of (2R,6R)-HNK are blocked in mice with a knockin of the BDNF Val66Met allele (which blocks the processing and activity-dependent release of BDNF) or by intra-mPFC microinjection of an anti-BDNF neutralizing antibody. Blockade of L-type voltage-dependent Ca2+ channels (VDCCs), required for activity-dependent BDNF release, also blocks the actions of (2R,6R)-HNK. Intra-mPFC infusion of pharmacol. inhibitors of TrkB or mTORC1 signaling, which are downstream of BDNF, also block the actions of (2R,6R)-HNK. Moreover, (2R,6R)-HNK increases synaptic function in the mPFC. These findings indicate that activity-dependent BDNF release and downstream TrkB and mTORC1 signaling, which increase synaptic function in the mPFC, are required for the rapid and long-lasting antidepressant effects of (2R,6R)-HNK, supporting the potential use of this metabolite for the treatment of MDD.
    15. 15
      Eckenhoff, R. G., Xi, J., Shimaoka, M., Bhattacharji, A., Covarrubias, M., and Dailey, W. P. (2010) Azi-Isoflurane, a Photolabel Analog of the Commonly Used Inhaled General Anesthetic Isoflurane. ACS Chem. Neurosci. 1 (2), 139– 145,  DOI: 10.1021/cn900014m
      15
      Azi-isoflurane, a Photolabel Analog of the Commonly Used Inhaled General Anesthetic Isoflurane
      Eckenhoff, Roderic G.; Xi, Jin; Shimaoka, Motomu; Bhattacharji, Aditya; Covarrubias, Manuel; Dailey, William P.
      ACS Chemical Neuroscience (2010), 1 (2), 139-145CODEN: ACNCDM; ISSN:1948-7193. (American Chemical Society)
      Volatility and low-affinity hamper an ability to define mol. targets of the inhaled anesthetics. Photolabels have proven to be a useful approach in this regard, although none have closely mimicked contemporary drugs. The authors report the synthesis and validation of azi-isoflurane, a compd. constructed by adding a diazirinyl moiety to the Me carbon of the commonly used general anesthetic isoflurane. Azi-isoflurane is slightly more hydrophobic than isoflurane, and more potent in tadpoles. This novel compd. inhibits Shaw2 K+ channel currents similarly to isoflurane and binds to apoferritin with enhanced affinity. Finally, when irradiated at 300 nm, azi-isoflurane adducts to residues known to line isoflurane-binding sites in apoferritin and integrin LFA-1, the only proteins with isoflurane binding sites defined by crystallog. This reagent should allow rapid discovery of isoflurane mol. targets and binding sites within those targets.
    16. 16
      Woll, K. A., Peng, W., Liang, Q., Zhi, L., Jacobs, J. A., Maciunas, L., Bhanu, N., Garcia, B. A., Covarrubias, M., Loll, P. J., Dailey, W. P., and Eckenhoff, R. G. (2017) Photoaffinity Ligand for the Inhalational Anesthetic Sevoflurane Allows Mechanistic Insight into Potassium Channel Modulation. ACS Chem. Biol. 12 (5), 1353– 1362,  DOI: 10.1021/acschembio.7b00222
      16
      Photoaffinity Ligand for the Inhalational Anesthetic Sevoflurane Allows Mechanistic Insight into Potassium Channel Modulation
      Woll, Kellie A.; Peng, Wesley; Liang, Qiansheng; Zhi, Lianteng; Jacobs, Jack A.; Maciunas, Lina; Bhanu, Natarajan; Garcia, Benjamin A.; Covarrubias, Manuel; Loll, Patrick J.; Dailey, William P.; Eckenhoff, Roderic G.
      ACS Chemical Biology (2017), 12 (5), 1353-1362CODEN: ACBCCT; ISSN:1554-8929. (American Chemical Society)
      Sevoflurane is a commonly used inhaled general anesthetic. Despite this, its mechanism of action remains largely elusive. Compared to other anesthetics, sevoflurane exhibits distinct functional activity. In particular, sevoflurane is a pos. modulator of voltage-gated Shaker-related potassium channels (Kv1.x), which are key regulators of action potentials. Here, we report the synthesis and validation of azisevoflurane, a photoaffinity ligand for the direct identification of sevoflurane binding sites in the Kv1.2 channel. Azisevoflurane retains major sevoflurane protein binding interactions and pharmacol. properties within in vivo models. Photoactivation of azisevoflurane induces adduction to amino acid residues that accurately reported sevoflurane protein binding sites in model proteins. Pharmacol. relevant concns. of azisevoflurane analogously potentiated wild-type Kv1.2 and the established mutant Kv1.2 G329T. In wild-type Kv1.2 channels, azisevoflurane photolabeled Leu317 within the internal S4-S5 linker, a vital helix that couples the voltage sensor to the pore region. A residue lining the same binding cavity was photolabeled by azisevoflurane and protected by sevoflurane in the Kv1.2 G329T. Mutagenesis of Leu317 in WT Kv1.2 abolished sevoflurane voltage-dependent pos. modulation. Azisevoflurane addnl. photolabeled a second distinct site at Thr384 near the external selectivity filter in the Kv1.2 G329T mutant. The identified sevoflurane binding sites are located in crit. regions involved in gating of Kv channels and related ion channels. Azisevoflurane has thus emerged as a new tool to discover inhaled anesthetic targets and binding sites and investigate contributions of these targets to general anesthesia.
    17. 17
      Vedula, L. S., Brannigan, G., Economou, N. J., Xi, J., Hall, M. A., Liu, R., Rossi, M. J., Dailey, W. P., Grasty, K. C., Klein, M. L., Eckenhoff, R. G., and Loll, P. J. (2009) A Unitary Anesthetic Binding Site at High Resolution. J. Biol. Chem. 284 (36), 24176– 24184,  DOI: 10.1074/jbc.M109.017814
      17
      A Unitary Anesthetic Binding Site at High Resolution
      Vedula, L. Sangeetha; Brannigan, Grace; Economou, Nicoleta J.; Xi, Jin; Hall, Michael A.; Liu, Renyu; Rossi, Matthew J.; Dailey, William P.; Grasty, Kimberly C.; Klein, Michael L.; Eckenhoff, Roderic G.; Loll, Patrick J.
      Journal of Biological Chemistry (2009), 284 (36), 24176-24184CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)
      Propofol is the most widely used injectable general anesthetic. Its targets include ligand-gated ion channels such as the GABAA receptor, but such receptor-channel complexes remain challenging to study at at. resoln. Until structural biol. methods advance to the point of being able to deal with systems such as the GABAA receptor, it will be necessary to use more tractable surrogates to probe the mol. details of anesthetic recognition. The authors have previously shown that recognition of inhalational general anesthetics by the model protein apoferritin closely mirrors recognition by more complex and clin. relevant protein targets; apoferritin also binds propofol and related GABAergic anesthetics, and that the same binding site mediates recognition of both inhalational and injectable anesthetics. Apoferritin binding affinities for a series of propofol analogs were found to be strongly correlated with the ability to potentiate GABA responses at GABAA receptors, validating this model system for injectable anesthetics. High resoln. x-ray crystal structures reveal that, despite the presence of hydrogen bond donors and acceptors, anesthetic recognition is mediated largely by van der Waals forces and the hydrophobic effect. Mol. dynamics simulations indicate that the ligands undergo considerable fluctuations about their equil. positions. Finally, apoferritin displays both structural and dynamic responses to anesthetic binding, which may mimic changes elicited by anesthetics in physiol. targets like ion channels.
    18. 18
      Oakley, S., Vedula, L. S., Bu, W., Meng, Q. C., Xi, J., Liu, R., Eckenhoff, R. G., and Loll, P. J. (2012) Recognition of Anesthetic Barbiturates by a Protein Binding Site: A High Resolution Structural Analysis. PLoS One 7 (2), e32070  DOI: 10.1371/journal.pone.0032070
      18
      Recognition of anesthetic barbiturates by a protein binding site: a high resolution structural analysis
      Oakley, Simon; Vedula, L. Sangeetha; Bu, Weiming; Meng, Qing Cheng; Xi, Jin; Liu, Renyu; Eckenhoff, Roderic G.; Loll, Patrick J.
      PLoS One (2012), 7 (2), e32070CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)
      Barbiturates potentiate GABA actions at the GABAA receptor and act as central nervous system depressants that can induce effects ranging from sedation to general anesthesia. No structural information has been available about how barbiturates are recognized by their protein targets. For this reason, we tested whether these drugs were able to bind specifically to horse spleen apoferritin, a model protein that has previously been shown to bind many anesthetic agents with affinities that are closely correlated with anesthetic potency. Thiopental, pentobarbital, and phenobarbital were all found to bind to apoferritin with affinities ranging from 10-500 μM, approx. matching the concns. required to produce anesthetic and GABAergic responses. X-ray crystal structures were detd. for the complexes of apoferritin with thiopental and pentobarbital at resolns. of 1.9 and 2.0 Å, resp. These structures reveal that the barbiturates bind to a cavity in the apoferritin shell that also binds haloalkanes, halogenated ethers, and propofol. Unlike these other general anesthetics, however, which rely entirely upon van der Waals interactions and the hydrophobic effect for recognition, the barbiturates are recognized in the apoferritin site using a mixt. of both polar and nonpolar interactions. These results suggest that any protein binding site that is able to recognize and respond to the chem. and structurally diverse set of compds. used as general anesthetics is likely to include a versatile mixt. of both polar and hydrophobic elements.
    19. 19
      Butts, C. A., Xi, J., Brannigan, G., Saad, A. A., Venkatachalan, S. P., Pearce, R. A., Klein, M. L., Eckenhoff, R. G., and Dmochowski, I. J. (2009) Identification of a Fluorescent General Anesthetic, 1-Aminoanthracene. Proc. Natl. Acad. Sci. U. S. A. 106 (16), 6501– 6506,  DOI: 10.1073/pnas.0810590106
      19
      Identification of a fluorescent general anesthetic, 1-aminoanthracene
      Butts, Christopher A.; Xi, Jin; Brannigan, Grace; Saad, Abdalla A.; Venkatachalan, Srinivasan P.; Pearce, Robert A.; Klein, Michael L.; Eckenhoff, Roderic G.; Dmochowski, Ivan J.
      Proceedings of the National Academy of Sciences of the United States of America (2009), 106 (16), 6501-6506CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      We identified a fluorophore, 1-aminoanthracene (1-AMA), that is anesthetic, potentiates GABAergic transmission, and gives an appropriate dissocn. const., Kd ≈ 0.1 mM, for binding to the general anesthetic site in horse spleen apoferritin (HSAF). 1-AMA fluorescence is enhanced when bound to HSAF. Thus, displacement of 1-AMA from HSAF by other anesthetics attenuates the fluorescence signal and allows detn. of Kd, as validated by isothermal titrn. calorimetry. This provides a unique fluorescence assay for compd. screening and anesthetic discovery. Addnl. electrophysiol. expts. in isolated cells indicate that 1-AMA potentiates chloride currents elicited by GABA, similar to many general anesthetics. Furthermore, 1-AMA reversibly immobilizes stage 45-50 Xenopus laevis tadpoles (EC50 = 16 μM) and fluorescence micrographs show 1-AMA localized to brain and olfactory regions. Thus, 1-AMA provides an unprecedented opportunity for studying general anesthetic distribution in vivo at the cellular and subcellular levels.
    20. 20
      Cohen, M. L. and Trevor, A. J. (1974) On the Cerebral Accumulation of Ketamine and the Relationship Between Metabolism of the Drug and Its Pharmacological Effects. J. Pharmacol. Exp. Ther. 189 (2), 351– 358
      20
      Cerebral accumulation of ketamine and the relation between metabolism of the drug and its pharmacological effects
      Cohen, Marlene L.; Trevor, Anthony J.
      Journal of Pharmacology and Experimental Therapeutics (1974), 189 (2), 351-8CODEN: JPETAB; ISSN:0022-3565.
      Rat brain slices accumulated and retained ketamine-HCl [1867-66-9] at concns. 2.3 times higher than those in the incubation medium. No selective binding of ketamine to subcellular components of rat brain homogenates was obsd. Detn. of the partition coeffs. of ketamine and its N-demethylated product (metabolite I)) indicated that both compds. were highly lipid sol. The i.v. injection of metabolite I into rats caused central nervous system effects including hypnosis, ataxia, and agitation, but of shorter duration than equiv. doses of ketamine. The pretreatment of rats with phenobarbital caused a 5-fold increase in the rats of ketamine metab. by hepatic tissue in vitro, whereas SKF 525A pretreatment inhibited ketamine metab. by 35% and prolonged the half-life of the drug in vivo.
    21. 21
      Onufriev, A. V. and Alexov, E. (2013) Protonation and PK Changes in Protein-Ligand Binding. Q. Rev. Biophys. 46 (2), 181– 209,  DOI: 10.1017/S0033583513000024
      21
      Protonation and pK changes in protein-ligand binding
      Onufriev, Alexey V.; Alexov, Emil
      Quarterly Reviews of Biophysics (2013), 46 (2), 181-209CODEN: QURBAW; ISSN:0033-5835. (Cambridge University Press)
      A review. Formation of protein-ligand complexes causes various changes in both the receptor and the ligand. This review focuses on changes in pK and protonation states of ionizable groups that accompany protein-ligand binding. Phys. origins of these effects are outlined, followed by a brief overview of the computational methods to predict them and the assocd. corrections to receptor-ligand binding affinities. Statistical prevalence, magnitude and spatial distribution of the pK and protonation state changes in protein-ligand binding are discussed in detail, based on both exptl. and theor. studies. While there is no doubt that these changes occur, they do not occur all the time; the estd. prevalence varies, both between individual complexes and by method. The changes occur not only in the immediate vicinity of the interface but also sometimes far away. When receptor-ligand binding is assocd. with protonation state change at particular pH, the binding becomes pH dependent: we review the interplay between sub-cellular characteristic pH and optimum pH of receptor-ligand binding. It is pointed out that there is a tendency for protonation state changes upon binding to be minimal at physiol. relevant pH for each complex (no net proton uptake/release), suggesting that native receptor-ligand interactions have evolved to reduce the energy cost assocd. with ionization changes. As a result, previously reported statistical prevalence of these changes - typically computed at the same pH for all complexes - may be higher than what may be expected at optimum pH specific to each complex. We also discuss whether proper account of protonation state changes appears to improve practical docking and scoring outcomes relevant to structure-based drug design. An overview of some of the existing challenges in the field is provided in conclusion.
    22. 22
      Vardy, E., Mosier, P. D., Frankowski, K. J., Wu, H., Katritch, V., Westkaemper, R. B., Aubé, J., Stevens, R. C., and Roth, B. L. (2013) Chemotype-Selective Modes of Action of κ-Opioid Receptor Agonists. J. Biol. Chem. 288 (48), 34470– 34483,  DOI: 10.1074/jbc.M113.515668
      22
      Chemotype-selective Modes of Action of κ-Opioid Receptor Agonists
      Vardy, Eyal; Mosier, Philip D.; Frankowski, Kevin J.; Wu, Huixian; Katritch, Vsevolod; Westkaemper, Richard B.; Aube, Jeffrey; Stevens, Raymond C.; Roth, Bryan L.
      Journal of Biological Chemistry (2013), 288 (48), 34470-34483CODEN: JBCHA3; ISSN:0021-9258. (American Society for Biochemistry and Molecular Biology)
      The crystal structures of opioid receptors provide a novel platform for inquiry into opioid receptor function. The mol. determinants for activation of the κ-opioid receptor (KOR) were studied using a combination of agonist docking, functional assays, and site-directed mutagenesis. Eighteen positions in the putative agonist binding site of KOR were selected and evaluated for their effects on receptor binding and activation by ligands representing four distinct chemotypes: the peptide dynorphin A(1-17), the arylacetamide U-69593, and the non-charged ligands salvinorin A and the octahydroisoquinolinone carboxamide 1xx. Minimally biased docking of the tested ligands into the antagonist-bound KOR structure generated distinct binding modes, which were then evaluated biochem. and pharmacol. Our anal. identified two types of mutations: those that affect receptor function primarily via ligand binding and those that primarily affect function. The shared and differential mechanisms of agonist binding and activation in KOR are further discussed. Usually, mutations affecting function more than binding were located at the periphery of the binding site and did not interact strongly with the various ligands. Anal. of the crystal structure along with the present results provide fundamental insights into the activation mechanism of the KOR and suggest that "functional" residues, along with water mols. detected in the crystal structure, may be directly involved in transduction of the agonist binding event into structural changes at the conserved rotamer switches, thus leading to receptor activation.
    23. 23
      Hustveit, O., Maurset, A., and Oye, I. (1995) Interaction of the Chiral Forms of Ketamine with Opioid, Phencyclidine, Sigma and Muscarinic Receptors. Pharmacol. Toxicol. 77 (6), 355– 359,  DOI: 10.1111/j.1600-0773.1995.tb01041.x
      23
      Interaction of the chiral forms of ketamine with opioid, phencyclidine, σ and muscarinic receptors
      Hustveit, Olav; Maurset, Atle; Oeye, Ivar
      Pharmacology & Toxicology (Copenhagen) (1995), 77 (6), 355-9CODEN: PHTOEH; ISSN:0901-9928. (Munksgaard)
      To elucidate the mechanisms of action of ketamine, the authors have investigated the binding of the chiral forms of ketamine to opioid (μ, δ and κ), phencyclidine, σ and muscarinic receptors and the authors have performed detailed concn.-response expts. in the guinea-pig ileum prepn. The affinity ratios for the chiral forms at phencyclidine, μ and κ receptors correlated with the potency ratio of the chiral forms in the ischemic pain test found previously. The affinities were highest for phencyclidine receptors. The affinities for muscarinic receptors were lower than for phencyclidine receptors by a factor of about 10-20. The concn.-response expts. revealed one opioid (naloxone sensitive) and one non-opioid component. The two components are very close, which explains why other authors have reported that naloxone antagonizes the ketamine effect only partly. The concns. of naloxone necessary to shift the opioid part of the curves indicate that ketamine is a κ agonist in the guinea-pig ileum prepn. The authors conclude that the analgesic effect of ketamine in humans is most probably mediated via phencyclidine receptors, although a κ effect can not be excluded. Binding to κ and muscarinic receptors may contribute to the psychotomimetic side effects seen during recovery from ketamine anesthesia.
    24. 24
      La Regina, A., Petrillo, P., Sbacchi, M., and Tavani, A. (1988) Interaction of U-69,593 with Mu-, Alpha- and Kappa-Opioid Binding Sites and Its Analgesic and Intestinal Effects in Rats. Life Sci. 42 (3), 293– 301,  DOI: 10.1016/0024-3205(88)90638-8
      24
      Interaction of U-69,593 with μ-, δ- and κ-opioid binding sites and its analgesic and intestinal effects in rats
      La Regina, A.; Petrillo, P.; Sbacchi, M.; Tavani, A.
      Life Sciences (1988), 42 (3), 293-301CODEN: LIFSAK; ISSN:0024-3205.
      The κ-opioid compd. U-69,593 was studied in rats in vitro in binding assays to assess its selectivity at the single types of opioid sites and in vivo to assess its analgesic activity and effect on intestinal propulsion. In vitro the U-69,593 inhibition curve of [3H]-(-)-bremazocine binding suppressed at μ- and δ-sites was biphasic and the inhibition const. (Ki) at the high-affinity site (10-18 nM) was 2 orders of magnitude smaller than the Ki at the low-affinity site. The Ki at μ- and .vdelta.-sites were resp. 3.3 and 8.5 μM. Thus [3H]-(-)-bremazocine, suppressed at μ- and δ-sites, may still bind more than 1 site, which U-69,593 might distinguish. In vivo U-69,593 i.p. prolonged the reaction time of rats on a 55° hot-plate and the dose of naloxone required to antagonize this effect was 40 times the dose that antagonized morphine-induced antinociception, suggesting the involvement of the κ-receptor. In the intestinal transit test U-69,593 at doses between 0.5 and 15 mg/kg i.p. only slightly slowed intestinal transit of a charcoal meal in rats with no dose-relation; it partly but significantly antagonized morphine-induced constipation. These results suggest that the κ-type of opioid receptor, with which U-69,593 interacts may induce analgesia, but has no appreciable role in the mechanisms of opioid-induced inhibition of intestinal transit in rats.
    25. 25
      McKinstry-Wu, A. R., Woll, K. A., Joseph, T. T., Bu, W., White, E. R., Bhanu, N. V., Garcia, B. A., Brannigan, G., Dailey, W. P., and Eckenhoff, R. G. (2019) Azi-Medetomidine: Synthesis and Characterization of a Novel A2 Adrenergic Photoaffinity Ligand. ACS Chem. Neurosci. 10 (11), 4716– 4728,  DOI: 10.1021/acschemneuro.9b00484
      25
      Azi-medetomidine: Synthesis and Characterization of a Novel α2 Adrenergic Photoaffinity Ligand
      McKinstry-Wu, Andrew R.; Woll, Kellie A.; Joseph, Thomas T.; Bu, Weiming; White, E. Railey; Bhanu, Natarajan V.; Garcia, Benjamin A.; Brannigan, Grace; Dailey, William P.; Eckenhoff, Roderic G.
      ACS Chemical Neuroscience (2019), 10 (11), 4716-4728CODEN: ACNCDM; ISSN:1948-7193. (American Chemical Society)
      Agonists at the α2 adrenergic receptor produce sedation, increase focus, provide analgesia, and induce centrally mediated hypotension and bradycardia, yet neither their dynamic interactions with adrenergic receptors nor their modulation of neuronal circuit activity is completely understood. Photoaffinity ligands of α2 adrenergic agonists have the potential both to capture discrete moments of ligand-receptor interactions and to prolong naturalistic drug effects in discrete regions of tissue in vivo. We present here the synthesis and characterization of a novel α2 adrenergic agonist photolabel based on the imidazole medetomidine called azi-medetomidine. Azi-medetomidine shares protein assocn. characteristics with its parent compd. in exptl. model systems and by mol. dynamics simulation of interactions with the α2A adrenergic receptor. Azi-medetomidine acts as an agonist at α2A adrenergic receptors, and produces hypnosis in Xenopus laevis tadpoles. Azi-medetomidine competes with the α2 agonist clonidine at α2A adrenergic receptors, which is potentiated by photolabeling, and azi-medetomidine labels moieties on the α2A adrenergic receptor as detd. by mass spectrometry in a manner consistent with a simulated model. This novel α2 adrenergic agonist photolabel can serve as a powerful tool for in vitro and in vivo investigations of adrenergic signaling.
    26. 26
      Andrade, C. (2017) Ketamine for Depression, 4: In What Dose, at What Rate, by What Route, for How Long, and at What Frequency?. J. Clin. Psychiatry 78 (7), e852  DOI: 10.4088/JCP.17f11738
      There is no corresponding record for this reference.
    27. 27
      Rasmussen, S. G. F., DeVree, B. T., Zou, Y., Kruse, A. C., Chung, K. Y., Kobilka, T. S., Thian, F. S., Chae, P. S., Pardon, E., Calinski, D., Mathiesen, J. M., Shah, S. T. A., Lyons, J. A., Caffrey, M., Gellman, S. H., Steyaert, J., Skiniotis, G., Weis, W. I., Sunahara, R. K., and Kobilka, B. K. (2011) Crystal Structure of the B2 Adrenergic Receptor-Gs Protein Complex. Nature 477 (7366), 549– 555,  DOI: 10.1038/nature10361
      27
      Crystal structure of the β2 adrenergic receptor-Gs protein complex
      Rasmussen, Soren G. F.; DeVree, Brian T.; Zou, Yao-Zhong; Kruse, Andrew C.; Chung, Ka-Young; Kobilka, Tong-Sun; Thian, Foon-Sun; Chae, Pil-Seok; Pardon, Els; Calinski, Diane; Mathiesen, Jesper M.; Shah, Syed T. A.; Lyons, Joseph A.; Caffrey, Martin; Gellman, Samuel H.; Steyaert, Jan; Skiniotis, Georgios; Weis, William I.; Sunahara, Roger K.; Kobilka, Brian K.
      Nature (London, United Kingdom) (2011), 477 (7366), 549-555CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
      G protein-coupled receptors (GPCRs) are responsible for the majority of cellular responses to hormones and neurotransmitters as well as the senses of sight, olfaction and taste. The paradigm of GPCR signalling is the activation of a heterotrimeric GTP binding protein (G protein) by an agonist-occupied receptor. The β2 adrenergic receptor (β2AR) activation of Gs, the stimulatory G protein for adenylyl cyclase, has long been a model system for GPCR signalling. Here we present the crystal structure of the active state ternary complex composed of agonist-occupied monomeric β2AR and nucleotide-free Gs heterotrimer. The principal interactions between the β2AR and Gs involve the amino- and carboxy-terminal α-helixes of Gs, with conformational changes propagating to the nucleotide-binding pocket. The largest conformational changes in the β2AR include a 14 Å outward movement at the cytoplasmic end of transmembrane segment 6 (TM6) and an α-helical extension of the cytoplasmic end of TM5. The most surprising observation is a major displacement of the α-helical domain of Gαs relative to the Ras-like GTPase domain. This crystal structure represents the first high-resoln. view of transmembrane signalling by a GPCR.
    28. 28
      Koehl, A., Hu, H., Maeda, S., Zhang, Y., Qu, Q., Paggi, J. M., Latorraca, N. R., Hilger, D., Dawson, R., Matile, H., Schertler, G. F. X., Granier, S., Weis, W. I., Dror, R. O., Manglik, A., Skiniotis, G., and Kobilka, B. K. (2018) Structure of the M-Opioid Receptor-G i Protein Complex. Nature 558 (7711), 547,  DOI: 10.1038/s41586-018-0219-7
      28
      Structure of the μ-opioid receptor-Gi protein complex
      Koehl, Antoine; Hu, Hongli; Maeda, Shoji; Zhang, Yan; Qu, Qianhui; Paggi, Joseph M.; Latorraca, Naomi R.; Hilger, Daniel; Dawson, Roger; Matile, Hugues; Schertler, Gebhard F. X.; Granier, Sebastien; Weis, William I.; Dror, Ron O.; Manglik, Aashish; Skiniotis, Georgios; Kobilka, Brian K.
      Nature (London, United Kingdom) (2018), 558 (7711), 547-552CODEN: NATUAS; ISSN:0028-0836. (Nature Research)
      The μ-opioid receptor (μOR) is a G-protein-coupled receptor (GPCR) and the target of most clin. and recreationally used opioids. The induced pos. effects of analgesia and euphoria are mediated by μOR signalling through the adenylyl cyclase-inhibiting heterotrimeric G protein Gi. Here we present the 3.5 Å resoln. cryo-electron microscopy structure of the μOR bound to the agonist peptide DAMGO and nucleotide-free Gi. DAMGO occupies the morphinan ligand pocket, with its N terminus interacting with conserved receptor residues and its C terminus engaging regions important for opioid-ligand selectivity. Comparison of the μOR-Gi complex to previously detd. structures of other GPCRs bound to the stimulatory G protein Gs reveals differences in the position of transmembrane receptor helix 6 and in the interactions between the G protein α-subunit and the receptor core. Together, these results shed light on the structural features that contribute to the Gi protein-coupling specificity of the μOR.
    29. 29
      Suomivuori, C.-M., Latorraca, N. R., Wingler, L. M., Eismann, S., King, M. C., Kleinhenz, A. L. W., Skiba, M. A., Staus, D. P., Kruse, A. C., Lefkowitz, R. J., and Dror, R. O. (2020) Molecular Mechanism of Biased Signaling in a Prototypical G Protein-Coupled Receptor. Science 367 (6480), 881– 887,  DOI: 10.1126/science.aaz0326
      29
      Molecular mechanism of biased signaling in a prototypical G protein-coupled receptor
      Suomivuori, Carl-Mikael; Latorraca, Naomi R.; Wingler, Laura M.; Eismann, Stephan; King, Matthew C.; Kleinhenz, Alissa L. W.; Skiba, Meredith A.; Staus, Dean P.; Kruse, Andrew C.; Lefkowitz, Robert J.; Dror, Ron O.
      Science (Washington, DC, United States) (2020), 367 (6480), 881-887CODEN: SCIEAS; ISSN:1095-9203. (American Association for the Advancement of Science)
      Biased signaling, in which different ligands that bind to the same G protein-coupled receptor preferentially trigger distinct signaling pathways, holds great promise for the design of safer and more effective drugs. Its structural mechanism remains unclear, however, hampering efforts to design drugs with desired signaling profiles. Here, we use extensive at.-level mol. dynamics simulations to det. how arrestin bias and G protein bias arise at the angiotensin II type 1 receptor. The receptor adopts two major signaling conformations, one of which couples almost exclusively to arrestin, whereas the other also couples effectively to a G protein. A long-range allosteric network allows ligands in the extracellular binding pocket to favor either of the two intracellular conformations. Guided by this computationally detd. mechanism, we designed ligands with desired signaling profiles.
    30. 30
      Yang, C., Kobayashi, S., Nakao, K., Dong, C., Han, M., Qu, Y., Ren, Q., Zhang, J., Ma, M., Toki, H., Yamaguchi, J., Chaki, S., Shirayama, Y., Nakazawa, K., Manabe, T., and Hashimoto, K. (2018) AMPA Receptor Activation-Independent Antidepressant Actions of Ketamine Metabolite (S)-Norketamine. Biol. Psychiatry 84 (8), 591– 600,  DOI: 10.1016/j.biopsych.2018.05.007
      30
      AMPA Receptor Activation-Independent Antidepressant Actions of Ketamine Metabolite (S)-Norketamine
      Yang, Chun; Kobayashi, Shizuka; Nakao, Kazuhito; Dong, Chao; Han, Mei; Qu, Youge; Ren, Qian; Zhang, Ji-chun; Ma, Min; Toki, Hidetoh; Yamaguchi, Jun-ichi; Chaki, Shigeyuki; Shirayama, Yukihiko; Nakazawa, Kazu; Manabe, Toshiya; Hashimoto, Kenji
      Biological Psychiatry (2018), 84 (8), 591-600CODEN: BIPCBF; ISSN:0006-3223. (Elsevier)
      Background: Ketamine, an N-methyl-D-aspartate receptor antagonist, exerts robust antidepressant effects in patients with treatment-resistant depression. The precise mechanisms underlying ketamine's antidepressant actions remain unclear, although previous research suggests that alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) activation plays a role. We investigated whether (S)-norketamine and (R)-norketamine, the two main metabolites of (R,S)-ketamine, also play a significant role in ketamine's antidepressant effects and whether the effects are mediated by AMPAR. Methods: Cellular mechanisms of antidepressant action of norketamine enantiomers were examd. in mice. Results: (S)-Norketamine had more potent antidepressant effects than (R)-norketamine in inflammation and chronic social defeat stress models. Furthermore, (S)-norketamine induced more beneficial effects on decreased dendritic spine d. and synaptogenesis in the prefrontal cortex and hippocampus compared with (R)-norketamine. Unexpectedly, AMPAR antagonists did not block the antidepressant effects of (S)-norketamine. The electrophysiol. data showed that, although (S)-norketamine inhibited N-methyl-D-aspartate receptor-mediated synaptic currents, (S)-norketamine did not enhance AMPAR-mediated neurotransmission in hippocampal neurons. Furthermore, (S)-norketamine improved redns. in brain-derived neurotrophic factor-tropomyosin receptor kinase B signaling in the prefrontal cortex of mice susceptible to chronic social defeat stress, whereas the tropomyosin receptor kinase B antagonist and a mechanistic target of rapamycin inhibitor blocked the antidepressant effects of (S)-norketamine. In contrast to (S)-ketamine, (S)-norketamine did not cause behavioral abnormalities, such as prepulse inhibition deficits, reward effects, loss of parvalbumin immunoreactivity in the medial prefrontal cortex, or baseline gamma-band oscillation increase. Conclusions: Our data identified a novel AMPAR activation-independent mechanism underlying the antidepressant effects of (S)-norketamine. (S)-Norketamine and its prodrugs could be novel antidepressants without the detrimental side effects of (S)-ketamine.
    31. 31
      Yokoyama, R., Higuchi, M., Tanabe, W., Tsukada, S., Naito, M., Yamaguchi, T., Chen, L., Kasai, A., Seiriki, K., Nakazawa, T., Nakagawa, S., Hashimoto, K., Hashimoto, H., and Ago, Y. (2020) (S)-Norketamine and (2S,6S)-Hydroxynorketamine Exert Potent Antidepressant-like Effects in a Chronic Corticosterone-Induced Mouse Model of Depression. Pharmacol., Biochem. Behav. 191, 172876,  DOI: 10.1016/j.pbb.2020.172876
      31
      (S)-norketamine and (2S,6S)-hydroxynorketamine exert potent antidepressant-like effects in a chronic corticosterone-induced mouse model of depression
      Yokoyama, Rei; Higuchi, Momoko; Tanabe, Wataru; Tsukada, Shinji; Naito, Megumi; Yamaguchi, Takumi; Chen, Lu; Kasai, Atsushi; Seiriki, Kaoru; Nakazawa, Takanobu; Nakagawa, Shinsaku; Hashimoto, Kenji; Hashimoto, Hitoshi; Ago, Yukio
      Pharmacology, Biochemistry and Behavior (2020), 191 (), 172876CODEN: PBBHAU; ISSN:0091-3057. (Elsevier)
      Clin. and preclin. studies have shown that the N-methyl-D-aspartate receptor antagonist ketamine exerts rapid and long-lasting antidepressant effects. Although ketamine metabolites might also have potential antidepressant properties, controversial results have been reported for (2R,6R)-hydroxynorketamine ((2R,6R)-HNK) in particular, and there is little information regarding the effects of other ketamine metabolites. Here we aimed to compare the effects of (R)-norketamine ((R)-NK), (S)-NK, (2R,6R)-HNK, and (2S,6S)-HNK in a mouse model of depression induced by chronic corticosterone (CORT) injection. None of the ketamine metabolites at doses up to 20 mg/kg showed antidepressant-like activity in naive male C57BL6/J mice. Chronic CORT treatment increased immobility in the forced swim test and caused anhedonic-like behaviors in the female encounter test. A single administration of (S)-NK and (2S,6S)-HNK dose-dependently reduced the enhanced immobility at 30 min after injection in chronic CORT-treated mice, while (R)-NK or (2R,6R)-HNK did not. Addnl., (S)-NK and (2S,6S)-HNK, but not (R)-NK or (2R,6R)-HNK, improved chronic CORT-induced anhedonia at 24 h after the injection. These results suggest that (S)-ketamine metabolites (S)-NK and (2S,6S)-HNK have potent acute and sustained antidepressant effects in rodents.
    32. 32
      Cui, X., Yeliseev, A., and Liu, R. (2013) Ligand Interaction, Binding Site and G Protein Activation of the Mu Opioid Receptor. Eur. J. Pharmacol. 702 (1–3), 309– 315,  DOI: 10.1016/j.ejphar.2013.01.060
      32
      Ligand interaction, binding site and G protein activation of the mu opioid receptor
      Cui, Xu; Yeliseev, Alexei; Liu, Renyu
      European Journal of Pharmacology (2013), 702 (1-3), 309-315CODEN: EJPHAZ; ISSN:0014-2999. (Elsevier B.V.)
      With the recently solved crystal structure of the murine mu opioid receptor, the elucidation of the structure function relationships of the human mu receptor becomes feasible. In this study, we analyzed the available structural information along with ligand binding and G protein activation of human mu receptor. Affinity detns. were performed in a HEK293 cell line stably transfected with the human mu opioid receptor for 6 different agonists (morphine, DAMGO, and herkinorn) and antagonists (naloxone, beta-Funaltrexamine, and Norbinaltorphimine). G protein activation was investigated in membrane prepns. contg. human mu receptors treated with the agonist, partial agonist, or antagonist compds. 4DKL.pdb was utilized for structural anal. and docking calcns. for 28 mu receptor ligands. The predicted affinities from docking were compared with those exptl. detd. While all known ligands bind to the receptor through the same binding site that is large enough to accommodate mols. of various sizes, interaction with D147 (D149 in human mu receptor) is essential for binding. No distinguishable interaction pattern in the binding site for agonist, partial agonist, or antagonist to predict pharmacol. activities was found. The failure to reconcile the predicted affinities from docking with exptl. values indicates that the receptor might undergo significant conformational changes from one state to the other states upon different ligand binding. A simplified model to understand the complicated system is proposed and further study on these multiple conformations using high resoln. structural approaches is suggested.
    33. 33
      Mafi, A., Kim, S.-K., and Goddard, W. A. (2020) The Atomistic Level Structure for the Activated Human κ-Opioid Receptor Bound to the Full Gi Protein and the MP1104 Agonist. Proc. Natl. Acad. Sci. U. S. A. 117 (11), 5836– 5843,  DOI: 10.1073/pnas.1910006117
      33
      The atomistic level structure for the activated human κ-opioid receptor bound to the full Gi protein and the MP1104 agonist
      Mafi, Amirhossein; Kim, Soo-Kyung; Goddard, William A., III
      Proceedings of the National Academy of Sciences of the United States of America (2020), 117 (11), 5836-5843CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      The kappa opioid receptor (kOR) is an important target for pain therapeutics to reduce depression and other harmful side effects of existing medications. The analgesic activity is mediated by kOR signaling through the adenylyl cyclase-inhibitory family of Gi protein. Here, we report the three-dimensional (3D) structure for the active state of human kOR complexed with both heterotrimeric Gi protein and MP1104 agonist. This structure resulted from long mol. dynamics (MD) and metadynamics (metaMD) simulations starting from the 3.1-Å X-ray structure of kOR-MP1104 after replacing the nanobody with the activated Gi protein and from the 3.5-Å cryo-EM structure of μOR-Gi complex after replacing the 168 missing residues. Using MD and metaMD we discovered interactions to the Gi protein with strong anchors to two intracellular loops and transmembrane helix 6 of the kOR. These anchors strengthen the binding, contributing to a contraction in the binding pocket but an expansion in the cytoplasmic region of κOR to accommodate G protein. These remarkable changes in κOR structure reveal that the anchors are essential for activation.
    34. 34
      Yamaguchi, J., Toki, H., Qu, Y., Yang, C., Koike, H., Hashimoto, K., Mizuno-Yasuhira, A., and Chaki, S. (2018) (2 R,6 R)-Hydroxynorketamine Is Not Essential for the Antidepressant Actions of (R)-Ketamine in Mice. Neuropsychopharmacology 43 (9), 1900– 1907,  DOI: 10.1038/s41386-018-0084-y
      34
      (2R,6R)-Hydroxynorketamine is not essential for the antidepressant actions of (R)-ketamine in mice
      Yamaguchi, Jun-ichi; Toki, Hidetoh; Qu, Youge; Yang, Chun; Koike, Hiroyuki; Hashimoto, Kenji; Mizuno-Yasuhira, Akiko; Chaki, Shigeyuki
      Neuropsychopharmacology (2018), 43 (9), 1900-1907CODEN: NEROEW; ISSN:0893-133X. (Nature Research)
      (R,S)-Ketamine has rapid and sustained antidepressant effects in depressed patients. Although the metab. of (R,S)-ketamine to (2 R,6 R)-hydroxynorketamine (HNK), a metabolite of (R)-ketamine, has been reported to be essential for its antidepressant effects, recent evidence suggests otherwise. The present study investigated the role of the metab. of (R)-ketamine to (2 R,6 R)-HNK in the antidepressant actions of (R)-ketamine. Antidepressant effects were evaluated using the forced swimming test in the lipopolysaccharide (LPS)-induced inflammation model of mice and the tail suspension test in naive mice. To prevent the metab. of (R)-ketamine to (2 R,6 R)-HNK, mice were pretreated with cytochrome P 450 (CYP) inhibitors. The concns. of (R)-ketamine, (R)-norketamine, and (2 R,6 R)-HNK in plasma, brain, and cerebrospinal fluid (CSF) samples were detd. using enantioselective liq. chromatog.-tandem mass spectrometry. The concns. of (R)-norketamine and (2 R,6 R)-HNK in plasma, brain, and CSF samples after administration of (R)-norketamine (10 mg/kg) and (2 R,6 R)-HNK (10 mg/kg), resp., were higher than those generated after administration of (R)-ketamine (10 mg/kg). Nonetheless, while (R)-ketamine attenuated, neither (R)-norketamine nor (2 R,6 R)-HNK significantly altered immobility times of LPS-treated mice. Treatment with CYP inhibitors prior to administration of (R)-ketamine increased the plasma levels of (R)-ketamine, while generation of (2 R,6 R)-HNK was almost completely blocked. (R)-Ketamine exerted the antidepressant effects at a lower dose in the presence of CYP inhibitors than in their absence, which is consistent with exposure levels of (R)-ketamine but not (2 R,6 R)-HNK. These results indicate that metab. to (2 R,6 R)-HNK is not necessary for the antidepressant effects of (R)-ketamine and that unmetabolized (R)-ketamine itself may be responsible for its antidepressant actions.
    35. 35
      Zanos, P., Moaddel, R., Morris, P. J., Georgiou, P., Fischell, J., Elmer, G. I., Alkondon, M., Yuan, P., Pribut, H. J., Singh, N. S., Dossou, K. S. S., Fang, Y., Huang, X.-P., Mayo, C. L., Wainer, I. W., Albuquerque, E. X., Thompson, S. M., Thomas, C. J., Zarate, C. A., and Gould, T. D. (2016) NMDAR Inhibition-Independent Antidepressant Actions of Ketamine Metabolites. Nature 533 (7604), 481– 486,  DOI: 10.1038/nature17998
      35
      NMDAR inhibition-independent antidepressant actions of ketamine metabolites
      Zanos, Panos; Moaddel, Ruin; Morris, Patrick J.; Georgiou, Polymnia; Fischell, Jonathan; Elmer, Greg I.; Alkondon, Manickavasagom; Yuan, Peixiong; Pribut, Heather J.; Singh, Nagendra S.; Dossou, Katina S. S.; Fang, Yuhong; Huang, Xi-Ping; Mayo, Cheryl L.; Wainer, Irving W.; Albuquerque, Edson X.; Thompson, Scott M.; Thomas, Craig J.; Zarate, Carlos A., Jr; Gould, Todd D.
      Nature (London, United Kingdom) (2016), 533 (7604), 481-486CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
      Major depressive disorder affects around 16% of the world population at some point in their lives. Despite the availability of numerous monoaminergic-based antidepressants, most patients require several weeks, if not months, to respond to these treatments, and many patients never attain sustained remission of their symptoms. The noncompetitive, glutamatergic NMDAR (N-methyl-D-aspartate receptor) antagonist (R,S)-ketamine exerts rapid and sustained antidepressant effects after a single dose in patients with depression, but its use is assocd. with undesirable side effects. Here the authors show that the metab. of (R,S)-ketamine to (2S,6S;2R,6R)-hydroxynorketamine (HNK) is essential for its antidepressant effects, and that the (2R,6R)-HNK enantiomer exerts behavioral, electroencephalog., electrophysiol. and cellular antidepressant-related actions in mice. These antidepressant actions are independent of NMDAR inhibition but involve early and sustained activation of AMPARs (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors). The authors also establish that (2R,6R)-HNK lacks ketamine-related side effects. The data implicate a novel mechanism underlying the antidepressant properties of (R,S)-ketamine and have relevance for the development of next-generation, rapid-acting antidepressants.
    36. 36
      Lumsden, E. W., Troppoli, T. A., Myers, S. J., Zanos, P., Aracava, Y., Kehr, J., Lovett, J., Kim, S., Wang, F.-H., Schmidt, S., Jenne, C. E., Yuan, P., Morris, P. J., Thomas, C. J., Zarate, C. A., Moaddel, R., Traynelis, S. F., Pereira, E. F. R., Thompson, S. M., Albuquerque, E. X., and Gould, T. D. (2019) Antidepressant-Relevant Concentrations of the Ketamine Metabolite (2R,6R)-Hydroxynorketamine Do Not Block NMDA Receptor Function. Proc. Natl. Acad. Sci. U. S. A. 116 (11), 5160– 5169,  DOI: 10.1073/pnas.1816071116
      36
      Antidepressant-relevant concentrations of the ketamine metabolite (2R,6R)-hydroxynorketamine do not block NMDA receptor function
      Lumsden, Eric W.; Troppoli, Timothy A.; Myers, Scott J.; Zanos, Panos; Aracava, Yasco; Kehr, Jan; Lovett, Jacqueline; Kim, Sukhan; Wang, Fu-Hua; Schmidt, Staffan; Jenne, Carleigh E.; Yuan, Peixiong; Morris, Patrick J.; Thomas, Craig J.; Zarate, Carlos A. Jr.; Moaddel, Ruin; Traynelis, Stephen F.; Pereira, Edna F. R.; Thompson, Scott M.; Albuquerque, Edson X.; Gould, Todd D.
      Proceedings of the National Academy of Sciences of the United States of America (2019), 116 (11), 5160-5169CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      Preclin. studies indicate that (2R,6R)-hydroxynorketamine (HNK) is a putative fast-acting antidepressant candidate. Although inhibition of NMDA-type glutamate receptors (NMDARs) is one mechanism proposed to underlie ketamine antidepressant and adverse effects, the potency of (2R,6R)-HNK to inhibit NMDARs has not been established. We used a multidisciplinary approach to det. the effects of (2R,6R)-HNK on NMDAR function. Antidepressant-relevant behavioral responses and (2R,6R)-HNK levels in the extracellular compartment of the hippocampus were measured following systemic (2R,6R)-HNK administration in mice. The effects of ketamine, (2R,6R)-HNK, and, in some cases, the (2S,6S)-HNK stereoisomer were evaluated on the following: (i) NMDA-induced lethality in mice, (ii) NMDAR-mediated field excitatory postsynaptic potentials (fEPSPs) in the CA1 field of mouse hippocampal slices, (iii) NMDAR-mediated miniature excitatory postsynaptic currents (mEPSCs) and NMDA-evoked currents in CA1 pyramidal neurons of rat hippocampal slices, and (iv) recombinant NMDARs expressed in Xenopus oocytes. While a single i.p. injection of 10 mg/kg (2R,6R)-HNK exerted antidepressant-related behavioral and cellular responses in mice, the ED50 of (2R,6R)-HNK to prevent NMDA-induced lethality was found to be 228 mg/kg, compared with 6.4 mg/kg for ketamine. The 10 mg/kg (2R,6R)-HNK dose generated maximal hippocampal extracellular concns. of 8 μM, which were well below concns. required to inhibit synaptic and extrasynaptic NMDARs in vitro. (2S,6S)-HNK was more potent than (2R,6R)-HNK, but less potent than ketamine at inhibiting NMDARs. These data demonstrate the stereoselectivity of NMDAR inhibition by (2R,6R;2S,6S)-HNK and support the conclusion that direct NMDAR inhibition does not contribute to antidepressant-relevant effects of (2R,6R)-HNK.
    37. 37
      Best, R. B., Zhu, X., Shim, J., Lopes, P. E. M., Mittal, J., Feig, M., and MacKerell, A. D. (2012) Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone ϕ, ψ and Side-Chain X1 and X2 Dihedral Angles. J. Chem. Theory Comput. 8 (9), 3257– 3273,  DOI: 10.1021/ct300400x
      37
      Optimization of the Additive CHARMM All-Atom Protein Force Field Targeting Improved Sampling of the Backbone .vphi., ψ and Side-Chain χ1 and χ2 Dihedral Angles
      Best, Robert B.; Zhu, Xiao; Shim, Jihyun; Lopes, Pedro E. M.; Mittal, Jeetain; Feig, Michael; MacKerell, Alexander D.
      Journal of Chemical Theory and Computation (2012), 8 (9), 3257-3273CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
      While the quality of the current CHARMM22/CMAP additive force field for proteins has been demonstrated in a large no. of applications, limitations in the model with respect to the equil. between the sampling of helical and extended conformations in folding simulations have been noted. To overcome this, as well as make other improvements in the model, we present a combination of refinements that should result in enhanced accuracy in simulations of proteins. The common (non-Gly, -Pro) backbone CMAP potential has been refined against exptl. soln. NMR data for weakly structured peptides, resulting in a rebalancing of the energies of the α-helix and extended regions of the Ramachandran map, correcting the α-helical bias of CHARMM22/CMAP. The Gly and Pro CMAPs have been refitted to more accurate quantum-mech. energy surfaces. Side-chain torsion parameters have been optimized by fitting to backbone-dependent quantum-mech. energy surfaces, followed by addnl. empirical optimization targeting NMR scalar couplings for unfolded proteins. A comprehensive validation of the revised force field was then performed against a collection of exptl. data: (i) comparison of simulations of eight proteins in their crystal environments with crystal structures; (ii) comparison with backbone scalar couplings for weakly structured peptides; (iii) comparison with NMR residual dipolar couplings and scalar couplings for both backbone and side-chains in folded proteins; (iv) equil. folding of mini-proteins. The results indicate that the revised CHARMM 36 parameters represent an improved model for modeling and simulation studies of proteins, including studies of protein folding, assembly, and functionally relevant conformational changes.
    38. 38
      Klauda, J. B., Venable, R. M., Freites, J. A., O’Connor, J. W., Tobias, D. J., Mondragon-Ramirez, C., Vorobyov, I., MacKerell, A. D., and Pastor, R. W. (2010) Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types. J. Phys. Chem. B 114 (23), 7830– 7843,  DOI: 10.1021/jp101759q
      38
      Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types
      Klauda, Jeffery B.; Venable, Richard M.; Freites, J. Alfredo; O'Connor, Joseph W.; Tobias, Douglas J.; Mondragon-Ramirez, Carlos; Vorobyov, Igor; MacKerell, Alexander D., Jr.; Pastor, Richard W.
      Journal of Physical Chemistry B (2010), 114 (23), 7830-7843CODEN: JPCBFK; ISSN:1520-6106. (American Chemical Society)
      A significant modification to the additive all-atom CHARMM lipid force field (FF) is developed and applied to phospholipid bilayers with both choline and ethanolamine contg. head groups and with both satd. and unsatd. aliph. chains. Motivated by the current CHARMM lipid FF (C27 and C27r) systematically yielding values of the surface area per lipid that are smaller than exptl. ests. and gel-like structures of bilayers well above the gel transition temp., selected torsional, Lennard-Jones and partial at. charge parameters were modified by targeting both quantum mech. (QM) and exptl. data. QM calcns. ranging from high-level ab initio calcns. on small mols. to semiempirical QM studies on a 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) bilayer in combination with exptl. thermodn. data were used as target data for parameter optimization. These changes were tested with simulations of pure bilayers at high hydration of the following six lipids: DPPC, 1,2-dimyristoyl-sn-phosphatidylcholine (DMPC), 1,2-dilauroyl-sn-phosphatidylcholine (DLPC), 1-palmitoyl-2-oleoyl-sn-phosphatidylcholine (POPC), 1,2-dioleoyl-sn-phosphatidylcholine (DOPC), and 1-palmitoyl-2-oleoyl-sn-phosphatidylethanolamine (POPE); simulations of a low hydration DOPC bilayer were also performed. Agreement with exptl. surface area is on av. within 2%, and the d. profiles agree well with neutron and x-ray diffraction expts. NMR deuterium order parameters (SCD) are well predicted with the new FF, including proper splitting of the SCD for the aliph. carbon adjacent to the carbonyl for DPPC, POPE, and POPC bilayers. The area compressibility modulus and frequency dependence of 13C NMR relaxation rates of DPPC and the water distribution of low hydration DOPC bilayers also agree well with expt. Accordingly, the presented lipid FF, referred to as C36, allows for mol. dynamics simulations to be run in the tensionless ensemble (NPT), and is anticipated to be of utility for simulations of pure lipid systems as well as heterogeneous systems including membrane proteins.
    39. 39
      Vanommeslaeghe, K. and MacKerell, A. D. (2012) Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing. J. Chem. Inf. Model. 52 (12), 3144– 3154,  DOI: 10.1021/ci300363c
      39
      Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing
      Vanommeslaeghe, K.; MacKerell, A. D.
      Journal of Chemical Information and Modeling (2012), 52 (12), 3144-3154CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Mol. mechanics force fields are widely used in computer-aided drug design for the study of drug-like mols. alone or interacting with biol. systems. In simulations involving biol. macromols., the biol. part is typically represented by a specialized biomol. force field, while the drug is represented by a matching general (org.) force field. In order to apply these general force fields to an arbitrary drug-like mol., functionality for assignment of atom types, parameters, and charges is required. In the present article, which is part I of a series of two, we present the algorithms for bond perception and atom typing for the CHARMM General Force Field (CGenFF). The CGenFF atom typer first assocs. attributes to the atoms and bonds in a mol., such as valence, bond order, and ring membership among others. Of note are a no. of features that are specifically required for CGenFF. This information is then used by the atom typing routine to assign CGenFF atom types based on a programmable decision tree. This allows for straight-forward implementation of CGenFF's complicated atom typing rules and for equally straight-forward updating of the atom typing scheme as the force field grows. The presented atom typer was validated by assigning correct atom types on 477 model compds. including in the training set as well as 126 test-set mols. that were constructed to specifically verify its different components. The program may be utilized via an online implementation at https://www.paramchem.org/.
    40. 40
      Vanommeslaeghe, K., Raman, E. P., and MacKerell, A. D. (2012) Automation of the CHARMM General Force Field (CGenFF) II: Assignment of Bonded Parameters and Partial Atomic Charges. J. Chem. Inf. Model. 52 (12), 3155– 3168,  DOI: 10.1021/ci3003649
      40
      Automation of the CHARMM General Force Field (CGenFF) II: Assignment of Bonded Parameters and Partial Atomic Charges
      Vanommeslaeghe, K.; Raman, E. Prabhu; MacKerell, A. D.
      Journal of Chemical Information and Modeling (2012), 52 (12), 3155-3168CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      Mol. mechanics force fields are widely used in computer-aided drug design for the study of drug candidates interacting with biol. systems. In these simulations, the biol. part is typically represented by a specialized biomol. force field, while the drug is represented by a matching general (org.) force field. In order to apply these general force fields to an arbitrary drug-like mol., functionality for assignment of atom types, parameters, and partial at. charges is required. In the present article, algorithms for the assignment of parameters and charges for the CHARMM General Force Field (CGenFF) are presented. These algorithms rely on the existing parameters and charges that were detd. as part of the parametrization of the force field. Bonded parameters are assigned based on the similarity between the atom types that define said parameters, while charges are detd. using an extended bond-charge increment scheme. Charge increments were optimized to reproduce the charges on model compds. that were part of the parametrization of the force field. Case studies are presented to clarify the functioning of the algorithms and the significance of their output data.
    41. 41
      Mayne, C. G., Saam, J., Schulten, K., Tajkhorshid, E., and Gumbart, J. C. (2013) Rapid Parameterization of Small Molecules Using the Force Field Toolkit. J. Comput. Chem. 34 (32), 2757– 2770,  DOI: 10.1002/jcc.23422
      41
      Rapid parameterization of small molecules using the force field toolkit
      Mayne, Christopher G.; Saam, Jan; Schulten, Klaus; Tajkhorshid, Emad; Gumbart, James C.
      Journal of Computational Chemistry (2013), 34 (32), 2757-2770CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
      The inability to rapidly generate accurate and robust parameters for novel chem. matter continues to severely limit the application of mol. dynamics simulations to many biol. systems of interest, esp. in fields such as drug discovery. Although the release of generalized versions of common classical force fields, for example, General Amber Force Field and CHARMM General Force Field, have posited guidelines for parameterization of small mols., many tech. challenges remain that have hampered their wide-scale extension. The Force Field Toolkit (ffTK), described herein, minimizes common barriers to ligand parameterization through algorithm and method development, automation of tedious and error-prone tasks, and graphical user interface design. Distributed as a VMD plugin, ffTK facilitates the traversal of a clear and organized workflow resulting in a complete set of CHARMM-compatible parameters. A variety of tools are provided to generate quantum mech. target data, setup multidimensional optimization routines, and analyze parameter performance. Parameters developed for a small test set of mols. using ffTK were comparable to existing CGenFF parameters in their ability to reproduce exptl. measured values for pure-solvent properties (<15% error from expt.) and free energy of solvation (±0.5 kcal/mol from expt.). © 2013 Wiley Periodicals, Inc.
    42. 42
      Joseph, T. T., Hénin, J., Eckenhoff, R. G., and Dmochowski, I. J. (2018) Molecular Mechanics Parameterization of Anesthetic Molecules. Methods in Enzymology 602, 61– 76,  DOI: 10.1016/bs.mie.2018.01.003
      42
      Molecular mechanics parameterization of anesthetic molecules
      Joseph, Thomas T.; Henin, Jerome
      Methods in Enzymology (2018), 602 (Chemical and Biochemical Approaches for the Study of Anesthetic Function, Part A), 61-76CODEN: MENZAU; ISSN:0076-6879. (Elsevier Inc.)
      A review. Anesthetic drug mols. are being increasingly studied through the use of computational methods such as mol. dynamics (MD). Mol. mechanics force fields require the investigator to supply parameters for the force field equation, which are not available for novel mols. Careful selection of these parameters is crit. for simulations to produce meaningful results. Therefore, this chapter presents a state-of-the-art method for detg. these parameters by comparison to quantum mechanics calcns. and exptl. quantities. Ketamine is used as an example to demonstrate the process.
    43. 43
      Joback, K. G. and Reid, R. C. (1987) Estimation of Pure-Component Properties from Group-Contributions. Chem. Eng. Commun. 57 (1–6), 233– 243,  DOI: 10.1080/00986448708960487
      43
      Estimation of pure-component properties from group contributions
      Joback, K. G.; Reid, R. C.
      Chemical Engineering Communications (1987), 57 (1-6), 233-43CODEN: CEGCAK; ISSN:0098-6445.
      For estg. the normal b.p., normal f.p., crit. consts. (temp., pressure, vol.), heat of formation (ideal gas at 298 K), Gibbs free energy of formation (ideal gas, unit fugacity, at 298 K), heat capacity (ideal gas), heat of vaporization (at the normal b.p.), heat of fusion, and liq. viscosity for a wide variety of org. compds., estn. equations for these properties and their numerical parameters (detd. by using existing exptl. data) are given for the contributions from 41 atoms or functional groups (including both ring and nonring increments), corresponding to simple increments of: (a) carbon and carbon-hydrogen groups, (b) halogens, (c) oxygen and oxygen-contg. groups, (d) nitrogen and nitrogen-contg. groups, and (e) sulfur and SH.
    44. 44
      Harrison, C. and Traynor, J. R. (2003) The [35S]GTPgammaS Binding Assay: Approaches and Applications in Pharmacology. Life Sci. 74 (4), 489– 508,  DOI: 10.1016/j.lfs.2003.07.005
      44
      The [35S]GTPγS binding assay: approaches and applications in pharmacology
      Harrison, C.; Traynor, J. R.
      Life Sciences (2003), 74 (4), 489-508CODEN: LIFSAK; ISSN:0024-3205. (Elsevier Science Inc.)
      A review. Receptors of the of seven transmembrane spanning, heterotrimeric G protein coupled family (GPCR) play crucial roles in regulating physiol. functions and consequently are targets for the action of many classes of drugs. Activation of receptor by agonist leads to the dissocn. of GDP from Gα of the Gαβγ heterotrimer, followed by the binding of GTP to Gα and subsequent modulation of downstream effectors. The G protein heterotrimer is reformed by GTPase activity of the Gα subunit, forming Gα-GDP and so allowing Gα and Gβγ to recombine. The [35S]GTPγS assay measures the level of G protein activation following agonist occupation of a GPCR, by detg. the binding of the non-hydrolyzable analog [35S]GTPγS to Gα subunits. Thus, the assay measures a functional consequence of receptor occupancy at one of the earliest receptor-mediated events. The assay allows for traditional pharmacol. parameters of potency, efficacy and antagonist affinity, with the advantage that agonist measures are not subjected to amplification or other modulation that may occur when analyzing parameters further downstream of the receptor. In general the assay is exptl. more feasible for receptors coupled to the abundant Gi/o proteins. Nevertheless, [35S]GTPγS binding assays are used with GPCRs that couple to the Gs and Gq families of G proteins, esp. in artificial expression systems, or using receptor-Gα constructs or immunopptn. of [35S]GTPγS-labeled Gα. The relative simplicity of the assay has made it very popular and its use is providing insights into contemporary pharmacol. topics including the roles of accessory proteins in signaling, constitutive activity of receptors and agonist specific signaling.
    45. 45
      Liu, R., Huang, X.-P., Yeliseev, A., Xi, J., and Roth, B. L. (2014) Novel Molecular Targets of Dezocine and Their Clinical Implications. Anesthesiol. J. Am. Soc. Anesthesiol. 120 (3), 714– 723,  DOI: 10.1097/ALN.0000000000000076
      There is no corresponding record for this reference.
    46. 46
      Kroeze, W. K., Sassano, M. F., Huang, X.-P., Lansu, K., McCorvy, J. D., Giguère, P. M., Sciaky, N., and Roth, B. L. (2015) PRESTO-Tango as an Open-Source Resource for Interrogation of the Druggable Human GPCRome. Nat. Struct. Mol. Biol. 22 (5), 362– 369,  DOI: 10.1038/nsmb.3014
      46
      PRESTO-Tango as an open-source resource for interrogation of the druggable human GPCRome
      Kroeze, Wesley K.; Sassano, Maria F.; Huang, Xi-Ping; Lansu, Katherine; McCorvy, John D.; Giguere, Patrick M.; Sciaky, Noah; Roth, Bryan L.
      Nature Structural & Molecular Biology (2015), 22 (5), 362-369CODEN: NSMBCU; ISSN:1545-9993. (Nature Publishing Group)
      G protein-coupled receptors (GPCRs) are essential mediators of cellular signaling and are important targets of drug action. Of the approx. 350 nonolfactory human GPCRs, more than 100 are still considered to be 'orphans' because their endogenous ligands remain unknown. Here, we describe a unique open-source resource that allows interrogation of the druggable human GPCRome via a G protein-independent β-arrestin-recruitment assay. We validate this unique platform at more than 120 nonorphan human GPCR targets, demonstrate its utility for discovering new ligands for orphan human GPCRs and describe a method (parallel receptorome expression and screening via transcriptional output, with transcriptional activation following arrestin translocation (PRESTO-Tango)) for the simultaneous and parallel interrogation of the entire human nonolfactory GPCRome.
    47. 47
      Huang, W., Manglik, A., Venkatakrishnan, A. J., Laeremans, T., Feinberg, E. N., Sanborn, A. L., Kato, H. E., Livingston, K. E., Thorsen, T. S., Kling, R. C., Granier, S., Gmeiner, P., Husbands, S. M., Traynor, J. R., Weis, W. I., Steyaert, J., Dror, R. O., and Kobilka, B. K. (2015) Structural Insights into M-Opioid Receptor Activation. Nature 524 (7565), 315– 321,  DOI: 10.1038/nature14886
      47
      Structural insights into μ-opioid receptor activation
      Huang, Weijiao; Manglik, Aashish; Venkatakrishnan, A. J.; Laeremans, Toon; Feinberg, Evan N.; Sanborn, Adrian L.; Kato, Hideaki E.; Livingston, Kathryn E.; Thorsen, Thor S.; Kling, Ralf C.; Granier, Sebastien; Gmeiner, Peter; Husbands, Stephen M.; Traynor, John R.; Weis, William I.; Steyaert, Jan; Dror, Ron O.; Kobilka, Brian K.
      Nature (London, United Kingdom) (2015), 524 (7565), 315-321CODEN: NATUAS; ISSN:0028-0836. (Nature Publishing Group)
      Activation of the μ-opioid receptor (μOR) is responsible for the efficacy of the most effective analgesics. To shed light on the structural basis for μOR activation, here we report a 2.1 Å X-ray crystal structure of the murine μOR bound to the morphinan agonist BU72 and a G protein mimetic camelid antibody fragment Nb39 (nanobody 39). The BU72-stabilized changes in the μOR binding pocket are subtle and differ from those obsd. for agonist-bound structures of the β2-adrenergic receptor (β2AR) and the M2 muscarinic receptor (M2R). Comparison with active β2AR reveals a common rearrangement in the packing of three conserved amino acids in the core of the μOR, and mol. dynamics simulations illustrate how the ligand-binding pocket is conformationally linked to this conserved triad. Addnl., an extensive polar network between the ligand-binding pocket and the cytoplasmic domains appears to play a similar role in signal propagation for all three G-protein-coupled receptors.
    48. 48
      Che, T., Majumdar, S., Zaidi, S. A., Ondachi, P., McCorvy, J. D., Wang, S., Mosier, P. D., Uprety, R., Vardy, E., Krumm, B. E., Han, G. W., Lee, M.-Y., Pardon, E., Steyaert, J., Huang, X.-P., Strachan, R. T., Tribo, A. R., Pasternak, G. W., Carroll, F. I., Stevens, R. C., Cherezov, V., Katritch, V., Wacker, D., and Roth, B. L. (2018) Structure of the Nanobody-Stabilized Active State of the Kappa Opioid Receptor. Cell 172 (1), 55– 67, e15.  DOI: 10.1016/j.cell.2017.12.011
      48
      Structure of the nanobody-stabilized active state of the Kappa opioid receptor
      Che, Tao; Majumdar, Susruta; Zaidi, Saheem A.; Ondachi, Pauline; McCorvy, John D.; Wang, Sheng; Mosier, Philip D.; Uprety, Rajendra; Vardy, Eyal; Krumm, Brian E.; Han, Gye Won; Lee, Ming-Yue; Pardon, Els; Steyaert, Jan; Huang, Xi-Ping; Strachan, Ryan T.; Tribo, Alexandra R.; Pasternak, Gavril W.; Carroll, F. Ivy; Stevens, Raymond C.; Cherezov, Vadim; Katritch, Vsevolod; Wacker, Daniel; Roth, Bryan L.
      Cell (Cambridge, MA, United States) (2018), 172 (1-2), 55-67.e15CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
      The κ-opioid receptor (KOP) mediates the actions of opioids with hallucinogenic, dysphoric, and analgesic activities. The design of KOP analgesics devoid of hallucinatory and dysphoric effects has been hindered by an incomplete structural and mechanistic understanding of KOP agonist actions. Here, we provide a crystal structure of human KOP in complex with the potent epoxymorphinan opioid agonist MP1104 and an active-state-stabilizing nanobody. Comparisons between inactive- and active-state opioid receptor structures reveal substantial conformational changes in the binding pocket and intracellular and extracellular regions. Extensive structural anal. and exptl. validation illuminate key residues that propagate larger-scale structural rearrangements and transducer binding that, collectively, elucidate the structural determinants of KOP pharmacol., function, and biased signaling. These mol. insights promise to accelerate the structure-guided design of safer and more effective κ-opioid receptor therapeutics.
    49. 49
      Wacker, D., Wang, S., McCorvy, J. D., Betz, R. M., Venkatakrishnan, A. J., Levit, A., Lansu, K., Schools, Z. L., Che, T., Nichols, D. E., Shoichet, B. K., Dror, R. O., and Roth, B. L. (2017) Crystal Structure of an LSD-Bound Human Serotonin Receptor. Cell 168 (3), 377– 389, e12.  DOI: 10.1016/j.cell.2016.12.033
      49
      Crystal structure of an LSD-bound human serotonin receptor
      Wacker, Daniel; Wang, Sheng; McCorvy, John D.; Betz, Robin M.; Venkatakrishnan, A. J.; Levit, Anat; Lansu, Katherine; Schools, Zachary L.; Che, Tao; Nichols, David E.; Shoichet, Brian K.; Dror, Ron O.; Roth, Bryan L.
      Cell (Cambridge, MA, United States) (2017), 168 (3), 377-389.e12CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
      The prototypical hallucinogen, LSD, acts via serotonin receptors, and here the authors describe the crystal structure of LSD in complex with human serotonin receptor 5-HT2B. The complex revealed conformational rearrangements to accommodate LSD, providing a structural explanation for the conformational selectivity of LSD's key diethylamide moiety. LSD dissocd. exceptionally slow from both 5-HT2BR and 5-HT2AR, a major target for its psychoactivity. Mol. dynamics (MD) simulations suggested that LSD's slow binding kinetics may be due to a "lid" formed by extracellular loop 2 (EL2) at the entrance to the binding pocket. A mutation predicted to increase the mobility of this lid greatly accelerated LSD's binding kinetics and selectively dampened LSD-mediated β-arrestin 2 recruitment. Thus, this study reveals an unexpected binding mode of LSD, illuminates key features of its kinetics, stereochem., and signaling, and provides a mol. explanation for LSD's actions at human serotonin receptors.
    50. 50
      Fiser, A. and Sali, A. (2003) ModLoop: Automated Modeling of Loops in Protein Structures. Bioinformatics 19 (18), 2500– 2501,  DOI: 10.1093/bioinformatics/btg362
      50
      ModLoop: automated modeling of loops in protein structures
      Fiser, Andras; Sali, Andrej
      Bioinformatics (2003), 19 (18), 2500-2501CODEN: BOINFP; ISSN:1367-4803. (Oxford University Press)
      Summary: ModLoop is a web server for automated modeling of loops in protein structures. The input is the at. coordinates of the protein structure in the Protein Data Bank format, and the specification of the starting and ending residues of one or more segments to be modeled, contg. no more than 20 residues in total. The output is the coordinates of the non-hydrogen atoms in the modeled segments. A user provides the input to the server via a simple web interface, and receives the output by e-mail. The server relies on the loop modeling routine in MODELLER that predicts the loop conformations by satisfaction of spatial restraints, without relying on a database of known protein structures. For a rapid response, ModLoop runs on a cluster of Linux PC computers.
    51. 51
      Jo, S., Kim, T., Iyer, V. G., and Im, W. (2008) CHARMM-GUI: A Web-Based Graphical User Interface for CHARMM. J. Comput. Chem. 29 (11), 1859– 1865,  DOI: 10.1002/jcc.20945
      51
      CHARMM-GUI: a web-based graphical user interface for CHARMM
      Jo, Sunhwan; Kim, Taehoon; Iyer, Vidyashankara G.; Im, Wonpil
      Journal of Computational Chemistry (2008), 29 (11), 1859-1865CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
      CHARMM is an academic research program used widely for macromol. mechanics and dynamics with versatile anal. and manipulation tools of at. coordinates and dynamics trajectories. CHARMM-GUI, http://www.charmm-gui.org, has been developed to provide a web-based graphical user interface to generate various input files and mol. systems to facilitate and standardize the usage of common and advanced simulation techniques in CHARMM. The web environment provides an ideal platform to build and validate a mol. model system in an interactive fashion such that, if a problem is found through visual inspection, one can go back to the previous setup and regenerate the whole system again. In this article, we describe the currently available functional modules of CHARMM-GUI Input Generator that form a basis for the advanced simulation techniques. Future directions of the CHARMM-GUI development project are also discussed briefly together with other features in the CHARMM-GUI website, such as Archive and Movie Gallery.
    52. 52
      Trott, O. and Olson, A. J. (2010) AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring Function, Efficient Optimization, and Multithreading. J. Comput. Chem. 31 (2), 455– 461,  DOI: 10.1002/jcc.21334
      52
      AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
      Trott, Oleg; Olson, Arthur J.
      Journal of Computational Chemistry (2010), 31 (2), 455-461CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
      AutoDock Vina, a new program for mol. docking and virtual screening, is presented. AutoDock Vina achieves an approx. 2 orders of magnitude speed-up compared with the mol. docking software previously developed in the authors' lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by the authors' tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calcs. the grid maps and clusters the results in a way transparent to the user.
    53. 53
      Phillips, J. C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., Chipot, C., Skeel, R. D., Kalé, L., and Schulten, K. (2005) Scalable Molecular Dynamics with NAMD. J. Comput. Chem. 26 (16), 1781– 1802,  DOI: 10.1002/jcc.20289
      53
      Scalable molecular dynamics with NAMD
      Phillips, James C.; Braun, Rosemary; Wang, Wei; Gumbart, James; Tajkhorshid, Emad; Villa, Elizabeth; Chipot, Christophe; Skeel, Robert D.; Kale, Laxmikant; Schulten, Klaus
      Journal of Computational Chemistry (2005), 26 (16), 1781-1802CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
      NAMD is a parallel mol. dynamics code designed for high-performance simulation of large biomol. systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical mol. dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temp. and pressure controls used. Features for steering the simulation across barriers and for calcg. both alchem. and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomol. system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the mol. graphics/sequence anal. software VMD and the grid computing/collab. software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu.
    54. 54
      Lenselink, E. B., Louvel, J., Forti, A. F., van Veldhoven, J. P. D., de Vries, H., Mulder-Krieger, T., McRobb, F. M., Negri, A., Goose, J., Abel, R., van Vlijmen, H. W. T., Wang, L., Harder, E., Sherman, W., Ijzerman, A. P., and Beuming, T. (2016) Predicting Binding Affinities for GPCR Ligands Using Free-Energy Perturbation. ACS Omega 1 (2), 293– 304,  DOI: 10.1021/acsomega.6b00086
      54
      Predicting Binding Affinities for GPCR Ligands Using Free-Energy Perturbation
      Lenselink, Eelke B.; Louvel, Julien; Forti, Anna F.; van Veldhoven, Jacobus P. D.; de Vries, Henk; Mulder-Krieger, Thea; McRobb, Fiona M.; Negri, Ana; Goose, Joseph; Abel, Robert; van Vlijmen, Herman W. T.; Wang, Lingle; Harder, Edward; Sherman, Woody; IJzerman, Adriaan P.; Beuming, Thijs
      ACS Omega (2016), 1 (2), 293-304CODEN: ACSODF; ISSN:2470-1343. (American Chemical Society)
      The rapid growth of structural information for G-protein-coupled receptors (GPCRs) has led to a greater understanding of their structure, function, selectivity, and ligand binding. Although novel ligands have been identified using methods such as virtual screening, computationally driven lead optimization has been possible only in isolated cases because of challenges assocd. with predicting binding free energies for related compds. Here, the authors provide a systematic characterization of the performance of free-energy perturbation (FEP) calcns. to predict relative binding free energies of congeneric ligands binding to GPCR targets using a consistent protocol and no adjustable parameters. Using the FEP+ package, first the authors validated the protocol, which includes a full lipid bilayer and explicit solvent, by predicting the binding affinity for a total of 45 different ligands across four different GPCRs (adenosine A2AAR, β1 adrenergic, CXCR4 chemokine, and δ opioid receptors). Comparison with exptl. binding affinity measurements revealed a highly predictive ranking correlation (av. spearman ρ = 0.55) and low root-mean-square error (0.80 kcal/mol). Next, the authors applied FEP+ in a prospective project, where the authors predicted the affinity of novel, potent adenosine A2A receptor (A2AR) antagonists. Four novel compds. were synthesized and tested in a radioligand displacement assay, yielding affinity values in the nanomolar range. The affinity of two out of the four novel ligands (plus three previously reported compds.) was correctly predicted (within 1 kcal/mol), including one compd. with approx. a 10-fold increase in affinity compared to the starting compd. Detailed analyses of the simulations underlying the predictions provided insights into the structural basis for the two cases where the affinity was overpredicted. Taken together, these results establish a protocol for systematically applying FEP+ to GPCRs and provide guidelines for identifying potent mols. in drug discovery lead optimization projects.
    55. 55
      Wang, J., Deng, Y., and Roux, B. (2006) Absolute Binding Free Energy Calculations Using Molecular Dynamics Simulations with Restraining Potentials. Biophys. J. 91 (8), 2798– 814,  DOI: 10.1529/biophysj.106.084301
      55
      Absolute binding free energy calculations using molecular dynamics simulations with restraining potentials
      Wang, Jiyao; Deng, Yuqing; Roux, Benoit
      Biophysical Journal (2006), 91 (8), 2798-2814CODEN: BIOJAU; ISSN:0006-3495. (Biophysical Society)
      The abs. (std.) binding free energy of eight FK506-related ligands to FKBP12 is calcd. using free energy perturbation mol. dynamics (FEP/MD) simulations with explicit solvent. A no. of features are implemented to improve the accuracy and enhance the convergence of the calcns. First, the abs. binding free energy is decompd. into sequential steps during which the ligand-surrounding interactions as well as various biasing potentials restraining the translation, orientation, and conformation of the ligand are turned "on" and "off.". Second, sampling of the ligand conformation is enforced by a restraining potential based on the root mean-square deviation relative to the bound state conformation. The effect of all the restraining potentials is rigorously unbiased, and it is shown explicitly that the final results are independent of all artificial restraints. Third, the repulsive and dispersive free energy contribution arising from the Lennard-Jones interactions of the ligand with its surrounding (protein and solvent) is calcd. using the Weeks-Chandler-Andersen sepn. This sepn. also improves convergence of the FEP/MD calcns. Fourth, to decrease the computational cost, only a small no. of atoms in the vicinity of the binding site are simulated explicitly, while all the influence of the remaining atoms is incorporated implicitly using the generalized solvent boundary potential (GSBP) method. With GSBP, the size of the simulated FKBP12/ligand systems is significantly reduced, from ∼25,000 to 2500. The computations are very efficient and the statistical error is small (∼1 kcal/mol). The calcd. binding free energies are generally in good agreement with available exptl. data and previous calcns. (within ∼2 kcal/mol). The present results indicate that a strategy based on FEP/MD simulations of a reduced GSBP at. model sampled with conformational, translational, and orientational restraining potentials can be computationally inexpensive and accurate.
    56. 56
      Deflorian, F., Perez-Benito, L., Lenselink, E. B., Congreve, M., van Vlijmen, H. W. T., Mason, J. S., Graaf de, C., and Tresadern, G. (2020) Accurate Prediction of GPCR Ligand Binding Affinity with Free Energy Perturbation. J. Chem. Inf. Model. 60 (11), 5563– 5579,  DOI: 10.1021/acs.jcim.0c00449
      56
      Accurate Prediction of GPCR Ligand Binding Affinity with Free Energy Perturbation
      Deflorian, Francesca; Perez-Benito, Laura; Lenselink, Eelke B.; Congreve, Miles; van Vlijmen, Herman W. T.; Mason, Jonathan S.; Graaf, Chris de; Tresadern, Gary
      Journal of Chemical Information and Modeling (2020), 60 (11), 5563-5579CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
      The computational prediction of relative binding free energies is a crucial goal for drug discovery, and G protein-coupled receptors (GPCRs) are arguably the most important drug target class. However, they present increased complexity to model compared to sol. globular proteins. Despite breakthroughs, exptl. X-ray crystal and cryo-EM structures are challenging to attain, meaning computational models of the receptor and ligand binding mode are sometimes necessary. This leads to uncertainty in understanding ligand-protein binding induced changes such as, water positioning and displacement, side chain positioning, hydrogen bond networks, and the overall structure of the hydration shell around the ligand and protein. In other words, the very elements that define structure activity relationships (SARs) and are crucial for accurate binding free energy calcns. are typically more uncertain for GPCRs. In this work we use free energy perturbation (FEP) to predict the relative binding free energies for ligands of two different GPCRs. We pinpoint the key aspects for success such as the important role of key water mols., amino acid ionization states, and the benefit of equilibration with specific ligands. Initial calcns. following typical FEP setup and execution protocols delivered no correlation with expt., but we show how results are improved in a logical and systematic way. This approach gave, in the best cases, a coeff. of detn. (R2) compared with expt. in the range of 0.6-0.9 and mean unsigned errors compared to expt. of 0.6-0.7 kcal/mol. We anticipate that our findings will be applicable to other difficult-to-model protein ligand data sets and be of wide interest for the community to continue improving FE binding energy predictions.
    57. 57
      Salari, R., Joseph, T., Lohia, R., Hénin, J., and Brannigan, G. (2018) A Streamlined, General Approach for Computing Ligand Binding Free Energies and Its Application to GPCR-Bound Cholesterol. J. Chem. Theory Comput. 14, 6560,  DOI: 10.1021/acs.jctc.8b00447
      57
      A Streamlined, General Approach for Computing Ligand Binding Free Energies and Its Application to GPCR-Bound Cholesterol
      Salari, Reza; Joseph, Thomas; Lohia, Ruchi; Henin, Jerome; Brannigan, Grace
      Journal of Chemical Theory and Computation (2018), 14 (12), 6560-6573CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
      The theory of receptor-ligand binding equil. has long been well-established in biochem., and was primarily constructed to describe dil. aq. solns. Accordingly, few computational approaches have been developed for making quant. predictions of binding probabilities in environments other than dil. isotropic soln. Existing techniques, ranging from simple automated docking procedures to sophisticated thermodn.-based methods, have been developed with sol. proteins in mind. Biol. and pharmacol. relevant protein-ligand interactions often occur in complex environments, including lamellar phases like membranes and crowded, nondilute solns. Here, the authors revisit the theor. bases of ligand binding equil., avoiding overly specific assumptions that are nearly always made when describing receptor-ligand binding. Building on this formalism, the authors extend the asymptotically exact Alchem. Free Energy Perturbation technique to quantifying occupancies of sites on proteins in a complex bulk, including phase-sepd., anisotropic, or nondilute solns., using a thermodynamically consistent and easily generalized approach that resolves several ambiguities of current frameworks. To incorporate the complex bulk without overcomplicating the overall thermodn. cycle, the authors simplify the common approach for ligand restraints by using a single distance-from-bound-configuration (DBC) ligand restraint during AFEP decoupling from protein. DBC restraints should be generalizable to binding modes of most small mols., even those with strong orientational dependence. The authors apply this approach to compute the likelihood that membrane cholesterol binds to known crystallog. sites on three GPCRs (β2-adrenergic, 5HT-2B, and μ-opioid) at a range of concns. Nonideality of cholesterol in a binary cholesterol:phosphatidylcholine (POPC) bilayer is characterized and consistently incorporated into the interpretation. The authors find that the three sites exhibit very different affinities for cholesterol: The site on the adrenergic receptor is predicted to be high affinity, with 50% occupancy for 1:109 CHOL:POPC mixts. The sites on the 5HT-2B and μ-opioid receptor are predicted to be lower affinity, with 50% occupancy for 1:103 CHOL:POPC and 1:102 CHOL:POPC, resp. These results could not have been predicted from the crystal structures alone.
    58. 58
      Lin, Y.-L., Aleksandrov, A., Simonson, T., and Roux, B. (2014) An Overview of Electrostatic Free Energy Computations for Solutions and Proteins. J. Chem. Theory Comput. 10 (7), 2690– 2709,  DOI: 10.1021/ct500195p
      58
      An Overview of Electrostatic Free Energy Computations for Solutions and Proteins
      Lin, Yen-Lin; Aleksandrov, Alexey; Simonson, Thomas; Roux, Benoit
      Journal of Chemical Theory and Computation (2014), 10 (7), 2690-2709CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
      A review. Free energy simulations for electrostatic and charging processes in complex mol. systems encounter specific difficulties owing to the long-range, 1/r Coulomb interaction. To calc. the solvation free energy of a simple ion, it is essential to take into account the polarization of nearby solvent but also the electrostatic potential drop across the liq.-gas boundary, however distant. The latter does not exist in a simulation model based on periodic boundary conditions because there is no phys. boundary to the system. An important consequence is that the ref. value of the electrostatic potential is not an ion in a vacuum. Also, in an infinite system, the electrostatic potential felt by a perturbing charge is conditionally convergent and dependent on the choice of computational conventions. Furthermore, with Ewald lattice summation and tinfoil conducting boundary conditions, the charges experience a spurious shift in the potential that depends on the details of the simulation system such as the vol. fraction occupied by the solvent. All these issues can be handled with established computational protocols, as reviewed here and illustrated for several small ions and three solvated proteins.
    59. 59
      Simonson, T. and Roux, B. (2016) Concepts and Protocols for Electrostatic Free Energies. Mol. Simul. 42 (13), 1090– 1101,  DOI: 10.1080/08927022.2015.1121544
      59
      Concepts and protocols for electrostatic free energies
      Simonson, Thomas; Roux, Benoit
      Molecular Simulation (2016), 42 (13), 1090-1101CODEN: MOSIEA; ISSN:0892-7022. (Taylor & Francis Ltd.)
      Electrostatic free energies play an essential role in numerous biomol. processes occurring in soln. Difficulties arise when the long-range Coulomb interaction is computed for idealised infinite simulation models with periodic boundary conditions. To maintain a neutral simulation box and a finite per-box energy, a neutralising charge d. or 'gellium' is commonly used, leading to a mean box potential that is constrained to be rigorously equal to zero at all times. Thus, in considering quantities such as ion solvation free energy, the potential drop to move from solvent into the usual, gas phase ref. state is missing. In fact, for an infinite mol. system, the electrostatic potential itself is not uniquely defined, but takes the form of an infinite series that is only conditionally convergent. This leads to several possible computational conventions that give different values for the potential and field, all math. valid. For exptl. measurable quantities, however, unique results are obtained when sufficiently large simulation boxes are utilized. These concepts are detailed, as well as a fundamental, linear response theor. framework that provides qual. understanding of the phys. processes involved, esp. dielec. relaxation of the environment in response to a new solute charge. Illustrative applications to ligand binding and biomol. electron transfer are described.
    60. 60
      Hummer, G., Pratt, L. R., and García, A. E. (1996) Free Energy of Ionic Hydration. J. Phys. Chem. 100 (4), 1206– 1215,  DOI: 10.1021/jp951011v
      60
      Free Energy of Ionic Hydration
      Hummer, Gerhard; Pratt, Lawrence R.; Garcia, Angel F.
      Journal of Physical Chemistry (1996), 100 (4), 1206-15CODEN: JPCHAX; ISSN:0022-3654. (American Chemical Society)
      The hydration free energies of ions exhibit an approx. quadratic dependence on the ionic charge, as predicted by the Born model. The authors analyze this behavior using second-order perturbation theory. This provides effective methods for calcg. free energies from equil. computer simulations. The av. and the fluctuation of the electrostatic potential at charge sites appear as the first coeffs. in a Taylor expansion of the free energy of charging. Combining the data from different charge states (e.g., charged and uncharged) allows calcn. of free-energy profiles as a function of the ionic charge. The first two Taylor coeffs. of the free-energy profiles can be computed accurately from equil. simulations, but they are affected by a strong system-size dependence. The authors apply corrections for these finite-size effects by using Ewald lattice summation and adding the self-interactions consistently. An analogous procedure is used for the reaction-field electrostatics. Results are presented for a model ion with methane-like Lennard-Jones parameters in simple point charge water. Two very closely quadratic regimes are found with different parameters for pos. and neg. ions. The hydration free energy of potassium, calcium, fluoride, chloride, and bromide ions are studied. The neg. ions are solvated more strongly (as measured by hydration free energies) compared to pos. ions of equal size, in agreement with exptl. data. The authors ascribe this preference of neg. ions to their strong interactions with water hydrogens, which can penetrate the ionic van der Waals shell without direct energetic penalty in the models used. In addn., they consistently find a pos. electrostatic potential at the center of uncharged Lennard-Jones particles in water, which also favors neg. ions. Regarding the effects of a finite system size, they show that even using only 16 water mols. it is possible to calc. accurately the hydration free energy of sodium, if self-interactions are considered.

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acschemneuro.0c00741.

    • Detailed derivation of the binding model for two ligand species, densities and enthalpies of vaporization/sublimation, residues, ligand pKa, fluorescence curves, docked conformations, RMSDs, free energy perturbation molecular dynamics energy plots, G-protein activation assays, Competition [35S]GTPgS assays, and β-arrestin recruitment assays (PDF)


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