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ArticleDecember 10, 2014

New Compstatin Peptides Containing N-Terminal Extensions and Non-Natural Amino Acids Exhibit Potent Complement Inhibition and Improved Solubility Characteristics
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Journal of Medicinal Chemistry

Cite this: J. Med. Chem. 2015, 58, 2, 814–826

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https://doi.org/10.1021/jm501345y

Published December 10, 2014

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Abstract

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Compstatin peptides are complement inhibitors that bind and inhibit cleavage of complement C3. Peptide binding is enhanced by hydrophobic interactions; however, poor solubility promotes aggregation in aqueous environments. We have designed new compstatin peptides derived from the W4A9 sequence (Ac-ICVWQDWGAHRCT-NH₂, cyclized between C2 and C12), based on structural, computational, and experimental studies. Furthermore, we developed and utilized a computational framework for the design of peptides containing non-natural amino acids. These new compstatin peptides contain polar N-terminal extensions and non-natural amino acid substitutions at positions 4 and 9. Peptides with α-modified non-natural alanine analogs at position 9, as well as peptides containing only N-terminal polar extensions, exhibited similar activity compared to W4A9, as quantified via ELISA, hemolytic, and cell-based assays, and showed improved solubility, as measured by UV absorbance and reverse-phase HPLC experiments. Because of their potency and solubility, these peptides are promising candidates for therapeutic development in numerous complement-mediated diseases.

Subjects

Introduction

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The complement system is implicated in the onset and progression of a number of autoinflammatory diseases. (1) Despite growing efforts to identify new complement-targeted therapeutics, only one (eculizumab, Alexion) is currently in the clinic. (2, 3) There is a growing need for new therapeutics to treat chronic inflammatory diseases, which include age-related macular degeneration (AMD), systemic lupus erythematosus, and rheumatoid arthritis, among many others. Most complement therapeutics currently in clinical development are biopharmaceuticals, which are prone to challenges in production, delivery, and bioavailability. Few attempts at developing low-molecular mass complement inhibitors have been successful, largely because of the fact that complement activation cascades are comprised of large protein–protein interfaces and multimolecular complexes. (3, 4)

Compstatin (Table 1, Parent) is a cyclic peptide that inhibits complement activation (reviewed in refs 2, 4−14). It is one of a small number of low molecular mass complement therapeutics in development. The peptide binds to complement component C3 (as well as its derivatives C3(H₂O), C3b, and C3c), the central protein of all complement activation cascades, and prevents its cleavage to C3a and C3b, thus blocking generation of complement effector proteins and complexes. Since its discovery, (5) the sequence of compstatin has been optimized to improve its affinity and complement inhibitory activity. (-8, 9, 15-30) Numerous sequence modifications led to the development of W4A9 (Table 1), the most active compstatin peptide with only natural amino acids. (20) Subsequently, many studies explored incorporation of non-natural amino acids and modifications to the compstatin sequence. (20, 22, 23, 26, 29, 30) Early studies of this type led to development of meW4A9 (Table 1), which is currently being pursued for treatment of AMD (clinicaltrials.gov, identifier numbers NCT00473928 and NCT01157065). (22)

Table 1. List of Compstatin Peptide Sequences^b

^{Table a}

Position refers to residue number within each compstatin sequence. For reference, the Cys residues are always at positions 2 and 12.

^{Table b}

Non-natural amino acid abbreviations: meW = l-1-methyltryptophan; Nal = l-1-naphthylalanine; Rea = R-α-ethylalanine; Aal = R-α-allylalanine; Sea = S-α-ethylalanine; 2Nl = l-2-naphthylalanine. All peptides (except linear) are cyclized by a disulfide bond between C2 and C12.

Determination of the structures of free (Parent) (15) and C3c-bound (W4A9) (31) compstatin peptides paved the way for further structure-based design and optimization of compstatin peptides. The solution NMR structure and subsequent structure–activity studies by NMR identified two opposite faces in compstatin, a hydrophobic face, proposed to be important for binding and inhibitory activity, and a polar face. (8, 9, 15, 17, 19) The cocrystal structure revealed that compstatin binding is dominated by hydrophobic interactions, accompanied by several hydrogen bonds. (31) Recent efforts (23-29) have focused on modifying amino acids at positions previously shown to tolerate mutations, (8, 9, 15, 17, 18, 32) but most designed peptides exhibited no significant improvement in inhibitory activity, and some had poor solubility. Consequently, molecular dynamics (MD) simulations were used to explore the possibility of incorporating additional polar amino acids at the compstatin (W4A9) N-terminus and N-terminal extensions. (27) Incorporation of hydrophilic amino acids has been recently reported to increase solubility of stapled peptides. (33) Indeed, incorporation of Arg at position 1 and Ser-Ser and Arg-Ser extensions at positions −1 and 0 showed similar inhibitory activity and improved solubility compared to W4A9. (28) This improvement is attributed to increased polarity at the N-terminus and the potential formation of additional polar contacts (hydrogen bonds and salt bridges) with C3c. (27, 28)

In this study, we sought to identify new compstatin peptides with sequence modifications that promote both potent complement inhibition and improved aqueous solubility. Upon the basis of results from our previous study, (28) we designed peptides with varied polar N-terminal extensions. In addition, we introduced a new computational approach for peptide design with non-natural amino acids. We incorporated non-natural amino acids (Figure 1) at positions 4 and 9, which were previously shown to be amenable for inhibitory activity optimization by the incorporation of non-natural amino acids. (20-22) These peptides, and combinations thereof, were screened in functional in vitro and cell-based assays for complement inhibitory activity and using absorbance spectroscopy and HPLC for solubility and hydrophobicity. We identified several new compstatin peptides with improved pharmacological properties for potential therapeutic development.

Figure 1. Chemical structures of non-natural amino acids in compstatin peptide sequences. The abbreviations used in sequences (Table 1) are shown in parentheses.

Results

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Building upon our recent studies, (24, 25, 27, 28) we designed new compstatin peptides with the aim of simultaneously improving inhibitory activity and aqueous solubility. Here, we incorporated components of de novo design, including a new method for incorporation of non-natural amino acids, rational design based on molecular dynamics simulations and previous experimental data, and structure–activity relations. The previously known top compstatin peptides, W4A9 and meW4A9, include modifications at positions 4 and 9 (relative to Parent), which enhance inhibitory activity by at least 10-fold in various functional assays. While these modifications enhance peptide inhibitory activity, they contribute to increased peptide hydrophobicity, which has led to aggregation in aqueous solution. Here, we introduced a new computational peptide design method, which allows for the introduction of non-natural amino acids, targeting positions 4 and 9 in order to promote sequence diversity and explore new sets of possible potent and soluble compstatin peptides. Peptides were evaluated based on predicted physical interactions (contacts, clashes, hydrogen bonds) with C3c and screened according to computationally predicted binding affinity (K*), relative to control peptides W4A9 and meW4A9 (Table S1 in Supporting Information). We identified three peptides with higher predicted binding affinity than both W4A9 and meW4A9 (peptides 1, 3, and 4), which were selected for experimental evaluation. In addition, peptides with similar non-natural modifications (peptides 2 and 5) were included in experimental evaluation as well (Table 1, set 1).

Our most recent study showed that the N-terminal sequence Arg-Ser-Ile forms additional polar and nonpolar contacts with C3c, based on results from molecular dynamics simulations. (27) Experimental data showed that peptide VI (from Gorham et al., 2013, sequence Ac-RSICV{meW}QDWGAHRCT-NH₂, cyclized by disulfide bridge) exhibited potent complement inhibition (in in vitro and cell based assays) and improved solubility (in UV absorption and RP-HPLC experiments). (28) Therefore, we screened combinations of polar amino acids in positions −1, 0, and 1 and evaluated predicted binding to C3c relative to control peptides (Table S2). Six peptides were identified with predicted C3c binding similar to or better than W4A9/meW4A9 (Table S3), and three of these were selected based on polarity (Table 1, set 2). In addition, the Arg-Ser-Ile extension was tested without meW at position 4 (Table 1, set 2).

Additionally, we selected components of both sets of peptides into two new sets, N-terminal extensions with Nal9 and N-terminal extensions with Nal4/9 (Table 1, sets 3 and 4). Set 3 peptides were selected in order to balance the potential interaction enhancement of Nal at position 9 with enhanced solubility from polar N-terminal extensions. Set 4 additionally included Nal at position 4, which was thought to improve hydrophobic contacts with C3. In light of our results from the first four sets of peptides and previous studies regarding compstatin modifications, (20) we combined selected features to design peptides with optimal binding and solubility (Table 1, set 5), and included Tyr at position 4 to improve solubility (Tyr4 was previously shown to enhance inhibitory activity like other aromatic amino acids at position 4). (18, 20, 32)

Complement Inhibition in ELISA and Hemolytic Assays

We evaluated 20 newly designed compstatin peptides (plus four controls) for complement inhibition in vitro. For each peptide, we measured the ability to inhibit formation of both C3b and C5b-9 in ELISA, as well as the ability to inhibit complement-mediated lysis of rabbit erythrocytes in hemolytic assays (Figure 2 and Table S4). We observe that for each peptide, inhibition of the different complement effectors occurs at similar concentration. This is in line with the ability of compstatin peptides to block all complement pathways at the C3 level and subsequent downstream activation. The newly designed peptides exhibit similar or slightly reduced inhibition (IC₅₀ values equal or higher) compared to meW4A9/W4A9 but were approximately an order of magnitude more potent than Parent. Notably, peptides 3–5 from set 1 (Figure 2A–C) and peptides 7–9 from set 2 (Figure 2D–F) show similar inhibitory activity compared to meW4A9/W4A9. This effect is also observed in the bar plots of Figure 3. α-Modified alanine analogs at position 9 (in peptides 3–5) are conservative substitutions, in terms of both C3 interaction and solubility, and thus have similar inhibitory activity to meW4A9/W4A9. Furthermore, polar N-terminal extensions seem to maintain inhibitory activity (as shown previously), (28) with the exception of peptide 6, in which the negatively charged Glu residue may destabilize intermolecular salt bridging interactions. All peptides containing Nal at position 9 (peptides 1, 2, and 10–17) required slightly higher concentrations for complement inhibition, likely because of higher aggregation propensity. However, some of the N-terminal extensions (i.e., Asn-Arg-Leu, peptides 12 and 16) improved inhibition of the Nal9 peptides (Figure 2G–L). The final set of peptides (set 5) showed improved complement inhibition (Figure 2M–O) but remained less potent compared to the aforementioned peptides from sets 1 and 2. Indeed, previous work has shown that incorporation of Tyr, Nal, or 2Nl at position 4 increased inhibitory activity relative to Parent but had slightly less activity compared to W4A9. (20) We hypothesized that addition of the polar RSI N-terminal extension may compensate for the aforementioned activity loss while simultaneously improving solubility. It seems that the extension neither improves nor diminishes inhibition, and therefore, the slightly reduced activity of set 5 peptides is most likely attributed to the substitutions at position 4. W4A9 has an IC₅₀ value approximately 1 order of magnitude better than Parent in all three assays (Figure 2P–R), which is in agreement with our previous data. (25, 28) Interestingly, we observe that meW4A9 has only slightly better inhibitory activity than W4A9 (within a 2-fold difference), which differs from previous studies that report nearly an order of magnitude difference in activity. (22, 23) We expect this discrepancy is due to differences in biochemical and functional assays used, as well as the aggregation propensity of meW4A9.

Figure 2. Concentration-dependent inhibition curves of compstatin peptides in C3b and C5b-9 ELISAs and hemolytic assays. Data show C3b, C5b-9, and hemolysis inhibition (from left to right) for set 1 (A–C), set 2 (D–F), set 3 (G–I), set 4 (J–L), set 5 (M–O), and control (P–R) peptides. Data points indicate mean percent inhibition ± SEM (standard error of the mean). The intersection of dashed lines shows the IC₅₀ value for meW4A9 in all plots. Curves to the right and left of the intersection point represent peptides with higher IC₅₀ values and lower IC₅₀ values compared to meW4A9, respectively.

Figure 3. IC₅₀ values for compstatin peptides. Bar plots show IC₅₀ values for compstatin peptides 1–20 and positive control peptides W4A9, meW4A9, and Parent in C3b ELISA (A), C5b-9 ELISA (B), and hemolytic assay (C). Bars show mean IC₅₀ from three independent runs of each experiment (±95% confidence interval). The dashed horizontal line shows the IC₅₀ value for the meW4A9 control peptide, for ease of comparison.

Complement Inhibition in Retinal Pigmented Epithelial Cell Model

A subset of peptides (peptides 5, 8, 12, 18, and 19) was selected for evaluation of complement inhibition in a retinal pigmented epithelial cell model, as described previously. (28) Selected peptides represent top-performing peptides from each set (1–5), as determined through ELISAs and hemolytic assays. All tested peptides significantly inhibited complement activation (C5b-9/ApoE fluorescence) at 1 μM concentration, compared to Linear and the positive control (serum without inhibitor), and displayed similar complement inhibition compared to W4A9 (Figure 4, Tables S5 and S6). Notably, there was no significant difference in the levels of complement activation between Parent and the positive control or the linear peptide at 1 μM. This is likely due to the fact that typical IC₅₀ values for Parent range between 4 and 13 μM in biochemical and functional assays (Figures 2 and 3, Table S4), and 1 μM concentration is not sufficient to reduce complement activation in RPE cells. To address this point, we tested higher concentrations of Parent in the in vitro RPE cell assay. While no complement inhibitory effects were noted for Parent at 1 or 10 μM, a significant (p-value of <0.001) inhibitory effect, similar to that of the W4A9 peptide at 1 μM, was observed for Parent at 50 μM (Figure 5). These results are consistent with the results of C3b and C5b-9 ELISA analyses of complement inhibition (Figure 2).

Figure 4. Effects of compstatin peptides on complement activation in the RPE cell in vitro assay. The ratio of C5b-9/ApoE fluorescence (±SEM, n = 10) is plotted as a percentage of the positive control (POS) for two hfRPE cell lines, 072810 (gray) and 081309 (black). Untreated cells that were not incubated with complement-competent human serum served as negative control (NEG). At 1 μM, the parent compound is not significantly different from the positive or linear peptide controls. All test peptides (W4A9, PEP 5, PEP 8, PEP 12, PEP 18, and PEP 19) displayed significant complement inhibition relative to their corresponding positive control (see Tables S5 and S6).

Figure 5. Effects of varying concentrations of Parent on complement activation in the RPE cell in vitro assay. The ratio of C5b-9/ApoE fluorescence (±SEM, n = 10) is plotted as a percentage of the positive control. Parent was tested at concentrations of 1, 10, and 50 μM (PAR1, PAR10, and PAR50). The concentration of W4A9 was 1 μM. All values are expressed relative to the positive control. Parent shows no significant difference from the positive control at 1 μM or 10 μM concentrations. At 50 μM the effect of Parent is equivalent to that of 1 μM W4A9. Both Parent at 50 μM and W4A9 at 1 μM are significantly different than the positive control (p-value of <0.001, two-tailed Mann–Whitney U test).

Solubility of Compstatin Peptides

Newly designed compstatin peptides were tested for solubility via absorbance measurements at 280 nm. The peptides showed a wide range of solubility, ranging from 0.1 to >5 mg/mL (Table S7). Control peptide meW4A9 showed moderate solubility in this assay (1.9 mg/mL), significantly lower than W4A9 and Parent, which exhibited apparent solubilities of 3.2 and 4.5 mg/mL, respectively. This result is consistent with the propensity of meW4A9 to aggregate in aqueous environments. (29, 34, 35) Peptides 1 and 2, which contain Nal at position 9, exhibited the poorest solubility (∼0.1 mg/mL), much lower than all control peptides. Addition of polar N-terminal extensions (peptides 10–17) improved solubility only slightly (<0.4 mg/mL). Peptides with α-modified alanine analogs at position 9 (peptides 3–5) showed much improved solubility, with values near the detection limit in this assay (and similar to W4A9 and Parent). These results show the importance of position 9 to compstatin solubility. Indeed, solubility ranking follows the trend Parent > W4A9 ∼ peptides 3–5 > peptides 1–2 ∼ peptides 10–17 and, in turn, His > Ala ∼ Rea ∼ Aal ∼ Sea > Nal at position 9. Thus, increased hydrophobicity of residues at position 9 strongly influences the solubility of compstatin peptides. As in the case of complement inhibition, set 5 peptides showed intermediate solubility. There is likely a balancing effect between the polar Arg-Ser-Ile N-terminal extension and the hydrophobic residue (Tyr, Nal, or 2Nl) at position 4. The importance of position 4 is also evidenced by decreased solubility of peptides containing meW at position 4 (peptide 2 and meW4A9). Interestingly, while peptide 18 was initially highly soluble (∼5 mg/mL), we observed a time-dependent decrease in concentration when stored in a polypropylene tube (Figure 6, Table S7). Thus, it is unclear whether the change in solubility of peptide 18 is due to time-dependent aggregation or simply interaction with the container. It should be noted that while complement inhibitory activity of compstatin peptides has been associated with increased hydrophobicity in past studies, (25, 28, 29) we observed that solubility is in fact associated with inhibitory activity (Figure 6). This is a direct result of our peptide design, as we engineered polar residues in regions of compstatin that should not affect binding. A clear exception to the aforementioned trend is Parent, in which solubility-enhancing substitutions are at positions that strongly influence binding.

Relative Lipophilicity of Compstatin Peptides

Modifications of peptide amino acid content can have a significant effect on peptide inhibitory activity, solubility, and lipophilicity. (36) The inhibitory activity of the compstatin peptides depends in part on hydrophobic interactions with C3, which can be mimicked by the interactions of hydrophobic amino acid side chains of the peptides with the C18 HPLC stationary phase. The retention time of each peptide on the HPLC column can be used to calculate logarithm of the retention factor (log(k)), which is related to its lipophilicity (and hydrophobicity). Figure 7 shows log(k) values for compstatin peptides. A full summary of RP-HPLC retention times, retention factors (k), and log(k) values are summarized in Table S8, with the peptides organized according to substitution patterns. The peptides are listed in order of increasing relative lipophilicity in Table S9. As expected, peptide lipophilicity is inversely related to solubility with an R² = 0.72 (Figure S1).

Figure 7. RP-HPLC retention factors for compstatin peptides. Bar plots show log(k) values for compstatin peptides 1–20 and positive control peptides W4A9, meW4A9, and Parent in C3b ELISA. The dashed horizontal line shows the log(k) value for the meW4A9 control peptide, for ease of comparison.

Modifications of peptide sequence can have a large effect on their RP-HPLC retention behavior. Comparison of the HPLC results for peptides 2 and 10–13 demonstrates that addition of the charged and polar amino acids at positions −1, 0, and 1 reduces the retention time while substitution of the hydrophobic l-1-naphthylalanine (Nal) for Trp increases the interaction with the stationary phase. Peptides 14–17 are more retained than peptides 10–13, which differ in structure only by a Nal substitution at position 4. Peptides 1 and 2 also contain Nal at position 9 in place of Ala in structurally similar peptides meW4A9 and W4A9, respectively, and are more highly retained than these analogs. A similar observation can be made when comparing peptides 9 and 19, which differ at position 4 by the substitution of Nal. Substitution of Tyr for Trp in peptide 18 reduces its interaction with the stationary phase as reflected by its smaller value of log(k).

Structural modifications of amino acid residues can also affect the interactions of peptides with the hydrophobic stationary phase. For example, the addition of a methyl group to a Trp residue at position 4 increases the retention compared with the Trp analogs. Peptides 1 and meW4A9 are more highly retained than peptides 2 and W4A9, respectively. The position of the naphthyl addition on alanine also affects the interaction of the peptide with the stationary phase. Peptide 19, which contains l-1-naphthylalanine, is less retained than peptide 20, which contains l-2-naphthylalanine at the same position. Similarly, peptides 3 and 5, which differ only by substitution of R- and S-α-ethylalanine, respectively, can be resolved by HPLC with peptide 3 being more highly retained than peptide 5.

Discussion

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Although continual efforts to improve compstatin have yielded peptides with potent complement inhibition, many are characterized by poor solubility in aqueous environments containing physiological ionic strength. (22, 25, 28, 29) The inhibitor meW4A9 (AL-78898A, Alcon) (29) has recently completed phase II clinical trials (clinicaltrials.gov, identifier numbers NCT00473928 and NCT01157065) for AMD; however, the results showed that this peptide did not yield reduced retinal thickness in AMD patients in comparison to ranibizumab (Genentech/Novartis), (14) a current AMD therapeutic. It is likely that the low aqueous solubility of meW4A9 contributes to its poor performance. (29, 34, 35) Thus, recent studies have aimed at improving solubility of compstatin peptides while simultaneously maintaining or improving complement inhibitory activity.

In this study, we designed and tested new compstatin peptides with diverse polar N-terminal substitutions and extensions. We also employed a new computational design framework for non-natural amino acids to identify non-natural amino acids at positions 4 and 9 predicted to improve C3 binding. Furthermore, we tested peptides containing combinations of these features, selected using rational design arguments. We note that all of our designed peptides have inhibitory activities similar to controls meW4A9 and W4A9 and significantly better than Parent (Figures 2–5). Most importantly, we found that peptides containing either α-modified non-natural alanine analogs at position 9 (peptides 3, 4, and 5) or N-terminal natural amino acid extensions (peptides 7, 8, and 9) have inhibitory activity similar to meW4A9 while exhibiting greatly improved aqueous solubility. Given the clinical interest in meW4A9 for treatment of a variety of complement-mediated disorders, in conjunction with problems recently encountered in clinical trials, we believe that our newly designed compstatin peptides (i.e., peptides 3, 4, 5, 7, 8, and 9) represent more promising therapeutic alternatives.

Several recent studies have focused on improving affinity of compstatin peptides. (23, 25, 26, 28, 29) Indeed, some compstatin peptides bind to C3 with affinities of <1 nM, with correspondingly low IC₅₀ values in complement assays. (29) While improved affinities are attractive for therapeutic design when taken at face value, we must remain aware that human plasma C3 concentrations are at least 5 μM, and thus high compstatin concentrations are required for therapeutic efficacy despite high binding affinity. Consequently, we conclude that (a) it is unnecessary to further improve compstatin binding affinity and inhibitory activity and (b) compstatin must be highly soluble to inhibit C3 cleavage in vivo. It is now crucial to focus on improving pharmacological properties of compstatin peptides. Recent studies have addressed several of these properties, including solubility, half-life, and degradation. (28-30, 37) We have identified several highly soluble compstatin peptides with potent inhibitory activity. In the past, it was thought that a high degree of hydrophobicity was required for potent compstatin activity. We illustrate here that the incorporation of N-terminal extensions can help to circumvent this activity–hydrophobicity/solubility paradigm. Our inhibitory activity versus solubility data (Figure 6) denote peptides with similar inhibitory activity compared to highly active controls (i.e., meW4A9) but with improved solubility characteristics. Furthermore, several peptides (peptides 6–9 and 18) are notably less lipophilic than both meW4A9 and W4A9 (Figure 7 and Table S9). These peptides, as well as additional peptides containing alternative combinations of top-performing modifications, represent promising candidates for therapeutic development, for treatment of a wide variety of complement-mediated autoinflammatory diseases.

Experimental Section

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De Novo Peptide Design with Natural Amino Acids

Sequence selection, fold specificity, and approximate binding affinity calculations for natural amino acid design were performed following the procedure described previously in Protein WISDOM and are described below. (38) The purpose of the design was to produce novel natural amino acid sequence extensions using the previously designed sequences Ac-RSICVWQDWGAHRCT-NH₂ (sequence of peptide 9 in Table 1, called RSI hereafter) and Ac-SSICVWQDWGAHRCT-NH₂ (27, 28) (called SSI hereafter) as templates. Both sequences are identical to the W4A9 variant of compstatin with two positions added to the N-terminus, termed positions −1 and 0. These sequences were used as input to further design these positions for C3c binding. RSI was chosen as a design template, as it previously yielded improved IC₅₀ values relative to W4A9 in C3b ELISA and hemolytic assays, as well as significant complement inhibition according to a human retinal pigmented epithelial cell-based model mimicking drusen biogenesis. (28) SSI had near W4A9 calculated affinity for human C3 and simultaneously high calculated affinity for non-primate C3. (27) Because of the previous designs of both of these sequences, MD simulations were previously performed and therefore were utilized as design templates in this next generation of design.

Sequence Selection

The peptide structure template for sequence selection was constructed based on the structure of the W4A9 analog (PDB code 2QKI). (31) Molecular dynamics simulations of the template compstatin extensions were performed previously and were used as a flexible template for this design. (28) In all cases, both extended positions, −1 and 0, as well as the adjacent position 1, were allowed to mutate. Because of the relatively small sequence space in this study (three mutatable positions only), the three positions were allowed to mutate to all possible amino acids except for proline and cysteine, which were excluded because of their unique chemical and geometric properties. The centroid–centroid potential energy function was used as the input force field, (39) which serves as a look-up table of energies of all combinations of amino acid pairs at a fixed set of distance bins.

The flexible distance–bin sequence selection method (38) was used to solve for a rank-ordered list of low energy sequences according to the following model.

(1a)subject to

(1b)

(1c)

(1d)

(1e)

(1f)The set i = 1, ..., n defines each residue position in the design template. At each position i, mutations are represented by j{i} = 1, ..., m_i, where m_i = 20 if the sequence position is allowed to mutate to any of the 20 natural amino acids. Alias sets k ≡ i and l ≡ j, with k >i, are used to represent the pairwise interactions between all residue positions and amino acid types. The decision variables y_i^j and y_k^l are solved for in order to determine the amino acid types in each position. The y_i^j variable will assume the value of 1 if the model assigns amino acid j to position i and assume the value of zero otherwise (similarly for y_k^l). The objective function represents the sum of all pairwise energy interactions in the design template. (38) The model incorporates the distance information from the template structures by introducing a binary variable b_ikd, which equals 1 if the distance between residues i and k falls within distance bin d and equals zero otherwise. The parameter disbin(x_i, x_k, d) equals 1 if the distance between residue positions i and k in any of the input template structures falls into distance bin d and equals zero otherwise, which forces only one distance bin per amino acid pair to contribute to the total energy. (38)

Since we started with template structures with sequences of both RSI and SSI, three separate runs were performed for the design. Run 1 used only the RSI structures as the input template. Run 2 used only SSI structures as the input template, and run 3 used a combined RSI and SSI structure set as the input template. For each run, 500 low-energy sequences were generated using the flexible distance–bin sequence selection method. From runs 1–3, a consensus set of sequences was constructed from the 1500 total sequences generated. This resulted in a total of 1019 sequences, which were then validated using the fold specificity metric. (38)

Fold Specificity

The aim of the fold specificity calculation is to determine the stability of a designed sequence in the target template structure as compared to the stability of the native sequence. The flexible template structure defined bounds on the minimum and maximum Cα–Cα distances and φ and ψ angles experienced. Ensembles are next generated using a torsion angle dynamics simulated annealing containing 500 conformers using CYANA 2.1. (40, 41) A local energy minimization is performed on every conformer in TINKER 3.6 (42) using the AMBER force field, (43) and the final potential energy of each conformer is tabulated. The energetics of the native sequence is similarly tabulated. The fold specificity calculation is next performed as

(2)with more positive values being favorable. (38)

Three separate runs of fold specificity were performed, based on which template structures were used in the calculation: run 1 using RSI structures only, run 2 using the SSI structures only, and run 3 using the combined RSI and SSI structure set. The sequences were then rank-ordered by fold specificity for each set, and a consensus set of sequences was determined for validation using approximate binding affinity (Table S2). Sequences were chosen for validation to maximize fold specificity across runs, as well as to cover a large chemical space. This resulted in 15 sequences with mutations in positions −1, 0, and 1 and in 7 sequences with mutations in positions −1 and 0 only.

Approximate Binding Affinity

The approximate binding affinity calculation in Protein WISDOM consists of several steps, which include diverse ligand ensemble generation, clustering, docking, and final ensemble generation. The goal is to generate a diverse ensemble of docked ligand poses to the receptor to assess the relative energetics of the complex, receptor, and ligand through calculation of approximations of their partition functions. The approximate binding affinity (44) is defined as K* = q_PL/(q_Pq_L), where q_PL = ∑_b∈B e^{–[E_b/(RT)]}, q_P = ∑_f∈F e^{–[E_f/(RT)]}, and q_L = ∑_l∈Le^{–[E_i/(RT)]} are the partition functions of the protein–ligand complex, the free protein, and ligand, respectively. The sets B, F, and L, contain rotamerically based conformations of the bound complex, free protein, and free ligand. E_n is the energy of each conformation. R is the gas constant, and T is the temperature.

Two-thousand structures for each candidate compstatin extension sequence are generated using the Rosetta AbRelax function as part of the Rosetta 3.4 package. (45-47) Monte Carlo sampling is used to replace local protein structures with structural fragments derived from homologous sequences. The structures are clustered based on their φ and ψ angles using OREO. (48, 49) The average structure from the 10 largest clusters and the lowest energy structure are chosen for docking to the target protein. This yields 11 structures with unique backbones which are next docked using RosettaDock. (50) The 10 lowest energy docked poses for each of the 11 ligands are passed to RosettaDesign (51) to generate 200 rotamer conformations per starting complex structure (22 000 total states representing the bound set). The ligand ensemble is constructed by taking the 10 lowest energy structures from each of the 10 largest clusters plus the 10 lowest overall energy peptide conformations and generating 200 rotamer conformations (22 000 free ligand structures) for each. The protein ensemble is generated directly by assembling 2000 rotamer structures from the single starting C3c structure. With these ensembles and their corresponding Rosetta energies, the K* is calculated.

The 22 sequences from fold specificity were run through the approximate binding affinity protocol (38) in order to determine which designed peptides were predicted to bind more strongly than the W4A9 peptide. Of the 22 tested peptides, six peptides were predicted to have higher binding affinity than W4A9 and peptide 9. The sequences of these peptides are provided in Table S3. Of these six peptides, three were selected for further experimental testing.

De Novo Peptide Design with Non-Natural Amino Acids

Recently, efforts have expanded to create methods for designing non-natural amino acids into proteins. (52-60) We have created new force fields based on quantum chemical calculations for post-translational modifications and unnatural amino acids for AMBER. (61, 62) Thus, we developed a novel framework combining our force fields, integer linear optimization, and molecular dynamics simulations to aid us in generating lead compounds for experimental exploration. The first step in the procedure is to derive candidate sequences containing post-translational modifications and non-natural amino acids. The overall idea is that we want to introduce modified amino acids to enhance the number of contacts and hydrogen bonds relative to the starting peptide while minimizing the clashes introduced by the modified amino acid. In addition, we want to preserve the local electrostatic landscape and any salt-bridges that are formed between the original or designed sequence scaffold and the target receptor. This is modeled as the following integer linear optimization problem:

(3a)subject to

(3b)

(3c)

(3d)

(3e)

(3f)

(3g)

(3h)with the following sets, parameters, and binary decision variables.

Sets:

p ∈ (1, 2, ..., Npositions); this is the set of positions in the amino acid sequence.

N_p ⊆ (Ala, Arg, Asn, ..., Tyr); this is the native amino acid in each position p.

M ∈ (N_p, ..., PTMs, ..., Non-naturalAminoAcids); this is the universe of modification types under consideration for which we have derived parameters for. This universe comes from a limited set of modifications parametrized early on for Forcefield_PTM (61) and Forcefield_NCAA. (62)

C ∈ (1, 2, 3, ..., N_complexes); this is the set of complex configurations.

Ω is the set of complex positions that correspond to the lowest energy configurations from a molecular dynamics simulation, an NMR structural ensemble, or a single crystal structure. Note that the set M contains all the post-translational modifications and unnatural amino acids for which we have parameters for, as well as the native amino acid in position p being designed. Modified amino acid parameters were taken from Forcefield_PTM (61) and Forcefield_NCAA. (62)

Parameters:

C_m^p, charge of modification m at position p.

D^p, charge of original amino acid on template sequence at position p.

H_m^p, hydrophobicity of modification m at position p.

H^p, hydrophobicity of original amino acid on template sequence at position p.

goodcontacts(C,m,p), number of contacts between modification m at position p and the receptor with van der Waals radii overlap of atoms (i,j) ≥ −2 in configuration C.

clashes(C,m,p), number of contacts between modification m at position p and adjacent residues in the peptide or the receptor with a van der Waals radii overlap of atoms (i,j) ≥ 0 or ≥ 0.4 if atoms (i,j) can potentially hydrogen bond in configuration C. (63)

hbonds(C,m,p), number of valid hydrogen bonds (distance and angle orientation) between modification m at position p and the receptor in configuration C. (63, 64)

IE(C,m,p), energy of binding between protein and peptide in configuration C as a result of modifying position p to modification type m, where this energy is defined as

sp(p) = 1 if position p is allowed to be modified, 0 otherwise.

S(C,m,p) = 0.1 goodcontacts(C,m,p) – 5 clashes(C,m,p) + 1 hbonds(C,m,p), weighted contact score of modification m at position p in configuration C. This score is not an energy that is physically derived but a tabulation of quantities of interactions.

Natural amino acids are classified as hydrophobic or hydrophilic if their relative side chain solvent-accessible surface areas (SASAs) calculated with the program NACCESS (65) in their position in three-dimensional space within the context of the complex are ≤20 or ≥50, in accordance with work by Bellows et al. (24) Introducing hydrophobicity constraints in previous designs using only natural amino acids was observed to be a critical component to successful design. (24, 66-69) Next, we define M_p ⊆ M, which is the subset of modifications meeting the charge and hydrophobicity constraints below at position p, ∀ positions p. This set, derived from the following constraints, reduces the search space.

Constraints That Must be Met for Inclusion in Set M_p

Local charge/salt-bridges must be conserved in each position p

(4)Local hydrophobicity must be conserved at each p

(5)

We further want to limit the modifications to those that are of the same type as the native amino acid in position p. For example, if the native amino acid in position 5 were a tyrosine, we would allow only for modifications of tyrosine as design choices and not modifications of alanine. Therefore, we define M_p^N_p ⊆ M_p as the subset of modifications in position p that are allowed given the native amino acid in position p, N_p. Utilizing this subset dramatically reduces the search space.

There are geometric conditions required for a contact, clash, and hydrogen bond to occur. These conditions reflect the fact that two atoms that hydrogen bond may come closer to each other than their van der Waals radii would normally allow. Contacts, clashes, and hydrogen bonds were evaluated between the modified position of the compstatin analog and C3c using custom scripts interfacing with UCSF Chimera. (64) Intermolecular contacts were defined with an overlap cutoff of −2 and a hydrogen bond allowance of 0. Both inter- and intramolecular clashes were calculated with an overlap cutoff of 0.4 and a hydrogen bond allowance of 0.4. Intermolecular hydrogen bonds were calculated between compstatin analogs and C3c with a 0.4 Å distance relaxation and a 20° angle relaxation from the default hydrogen bond criteria.

Binary Decision Variables

y_m^p = 1 if modification m is assigned to position p, 0 otherwise.

The objective function, eq 3a, aims to maximize a Boltzmann-weighted contact score. Equation 3b defines the weights of the contact score as a weighted sum of goodcontacts, clashes, and hbonds. The goal of the contact score is to improve affinity/specificity through the optimization of shape-complementarity at the individual amino acid level. It rewards good contacts and hydrogen bonds while strongly penalizing unfavorable clashes. Equation 3c defines a position-specific partition function. This quantity becomes the denominator for the Boltzmann-weighted contact score so that for each position, a probability can be derived based on the sum over the allowed modification types m ∈ M_p^N_p and complex configurations C. Equation 3d defines the Boltzmann factor that is the ratio of the exponent of the weighted contact score, eq 3b divided by the position-specific partition function, eq 3c. The constraint 3e states that the average energy of binding across all complex configurations must remain favorable for the modification m to be chosen in position p. This is important to preserve the local electrostatic interactions of the template sequence if any are present. Equation 3f states that only one amino acid is allowed to be selected in each position. Equation 3g is the integer cut constraints that generate a rank-ordered list of optimal solutions. Equation 3h indicates that the decision variables y_m^p are binary.

A computational pipeline to design proteins and peptides by introducing non-natural amino acids was created. The pipeline takes as input design positions, as well as a set of complex configurations corresponding to a peptide with natural amino acids bound to a receptor protein. These configurations were the single state of the C3c:W4A9 crystal structure (PDB code 2QKI). (31) Trp4 and Ala9 were selected as design positions. Next, the initial energy of binding, charge, and hydrophobicity constraints are populated using AMBER 11 (70) and Chimera. (64) Then for each complex configuration and each allowed modification in each design position, the complex is modified at the specified design position, a local energy minimization is performed, and the contacts, clashes, hydrogen bonds, and binding energies are populated. The AMBER program tleap was used to construct the modified side chains according to their orientations defined in Forcefield_PTM (61) and Forcefield_NCAA. (62) In position 4, tryptophan, 5-hydroxytryptophan, 5-methyltryptophan, N-methyltryptophan, 1-methyltryptophan, and 7-hydroxytrptophan were evaluated. In position 9, alanine, 1-naphthylalanine, N-methylalanine, pyrenylalanine, (R)-α-ethylalanine, (S)-α-ethylalanine, and R(+)-α-allylalanine were evaluated. These were chosen as they met the criteria to be included in each of their respective sets M_P^N_P, and their parameters were included in Forcefield_PTM or Forcefield_NCAA. For each modification upon construction, 1500 steps of steepest descent followed by 500 steps of conjugate gradient minimization were performed to relax the new non-natural side chain placement in the context of compstatin and the C3c receptor. The implicit solvent model by Onufriev (71, 72) (igb = 5) was utilized in all AMBER calculations. After population of this information for all complex configurations, the integer linear optimization model presented above is solved to global optimality, generating a rank-ordered list of modified amino acid substitutions.

The sequence solutions were next simulated in AMBER 11 to assess the approximate binding affinity (K*) with a procedure described previously. (62) Specifically, three independent simulations are carried out of the complex, protein, and peptide. A single simulation of the protein was used to assess its energetic contributions. Structures were minimized with 600 steps of steepest descent with 400 steps of conjugate gradient minimization to relax the new side chains. The structures were heated in six stages over 30 ps from 0 to 300 K. Shake constraints were used for all simulation steps on the heavy-atom to hydrogen bonds, and a nonbonded interaction cutoff of 16 Å was used. Each C3c:compstatin peptide candidate sequence underwent short 0.5 ns production simulations using a 1 fs time step at 300 K. The theoretical foundation for this calculation was previously described in Khoury et al. (62) and Lilien et al. (44) Those sequences with the highest K* values relative to the control peptide W4A9 were proposed for experimental testing (Table S1). We note that the approximate binding affinity is used as a metric to select which peptides may be promising (62) candidates for testing based on physics-based potentials, and we do not attempt to compare the calculated values to the exact experimental values. Instead, we aim to utilize metrics that increase our probability that top ranked peptides are indeed inhibitors of C3.

Peptide Synthesis

Compstatin peptides 1–9, 14–20, W4A9, meW4A9, and Parent were synthesized by WuXi AppTec (Shanghai, China). Peptides 10–13 were synthesized by Genscript, Inc. (Piscataway, NJ, USA). Linear (negative control) was obtained from either Tocris Bioscience (Bristol, U.K.) or WuXi AppTec. All peptides were of >95% purity, as determined by HPLC and MS. Non-natural amino acids used in this study included l-1-methyltryptophan, l-1-naphthylalanine, l-2-naphthylalanine, R-α-ethylalanine, R-α-allylalanine, and S-α-ethylalanine (Figure 1). Peptides containing l-1-methyltryptophan were synthesized using Fmoc-1-methyl-dl-tryptophan (commercially available preparation) and subsequently purified by HPLC.

Solubility Measurements

Approximately 1 mg of each tested peptide was dissolved in 200 μL of PBS, pH 7.4. It should be noted that the resulting concentration yields saturated solutions for only some peptides, and the maximum solubility reported here is thus 5 mg/mL. Samples were vortexed for 30 s each, then centrifuged at 13000g for 5 min. Supernatant was collected and measured spectrophotometrically at 280 nm, using a NanoDrop Lite spectrophotometer. Absorbance measurements were converted to concentration using the Beer–Lambert law. Molar extinction coefficients were calculated for each peptide based on the number of Trp and Tyr residues in their sequences. Because of their aromatic properties, l-1-methyltryptophan, l-1-naphthylalanine, and l-2-naphthylalanine also contribute to absorbance at 280 nm. Molar extinction coefficients used for these amino acids were 5470 M^–1 cm^–1, (28) 3936 M^–1 cm^–1, (20) and 3936 M^–1 cm^–1, respectively (the coefficient for l-2-naphthylalanine was assumed to be equal to that of l-1-naphthylalanine). Dissolved samples were stored at 4 °C, and measurements of the same samples were repeated at 24 and 48 h time points. Measurements represent the mean and standard deviation of three measurements performed on the each sample.

C3b and C5b-9 ELISA

Nunc Maxisorp 96-well microtiter plates were coated with 20 μg/mL lipopolysaccharides (LPS) from Salmonella enterica serotype enteritidis (Sigma-Aldrich, St. Louis, MO, USA) for 16 h at ambient temperature. Plates were washed three times with PBS (containing 0.05% Tween-20; PBS-T) between each incubation step. Plates were blocked with 4% BSA in PBS-T for 1 h at 37 °C. Lyophilized compstatin peptides were initially dissolved in PBS, pH 7.4, and concentration was measured spectrophotometrically at 280 nm. Serial dilutions of each peptide were prepared in veronal-buffered saline containing 0.1% gelatin, 5 mM MgCl₂, and 10 mM EGTA (GVBS-MgEGTA). Normal human serum (Complement Technology, Inc., Tyler, TX, USA) was dissolved in GVBS-MgEGTA and was preincubated with peptide dilutions (or buffer) for 15 min at ambient temperature. Samples were subsequently incubated in blocked plates for 1 h at 37 °C. After incubation, plates were incubated with either horseradish peroxidase (HRP) conjugated anti-C3 (MP Biomedicals, Solon, OH, USA) or anti-C5b-9 aE11 (Abcam, Cambridge, MA, USA) for 1 h at 37 °C. C5b-9 detection additionally involved incubation with an HRP-conjugated secondary antibody, also for 1 h at 37 °C. Levels of C3b and C5b-9 deposition were measured using a 3,3′,5,5′-tetramethylbenzidine substrate solution containing urea hydrogen peroxide in 0.11 M sodium acetate buffer, followed by addition of 1 N H₂SO₄. Plates were subsequently measured spectrophotometrically at 450 nm.

Hemolytic Assays

Rabbit erythrocytes (Complement Technology, Inc., Tyler, TX, USA) were washed and resuspended in veronal-buffered saline containing 5 mM MgCl₂ and 10 mM EGTA (VBS-MgEGTA). Normal human serum and compstatin peptides (serial dilutions) were diluted in VBS-MgEGTA and preincubated together in round-bottom 96-well plates for 15 min at ambient temperature. 5 × 10⁶ rabbit erythrocytes were added to each well, and plates were incubated for 20 min at 37 °C. Erythrocytes in either deionized water or normal human serum (dissolved in VBS-MgEGTA) were used as positive controls for lysis, and erythrocytes in either VBS-MgEGTA or normal human serum (dissolved in VBS-EDTA) were used as negative controls for lysis. Reactions were quenched by adding ice cold VBS (containing 50 mM EDTA) to each well. Plates were centrifuged at 1000g for 5 min, and supernatant was diluted 1:1 in deionized water in new plates. Lysis was quantified spectrophotometrically at 405 nm.

RPE Cell Culture

The RPE cell-based in vitro model of drusen formation (73) was employed as previously described. (28) Human fetal RPE cells (Advanced Bioscience Resources, Alameda, CA) were cultured on Millipore HA porous supports (Millipore, catalog no. PIHA 01250) in Miller medium supplemented with 5% fetal calf serum (FCS). RPE cell cultures derived from two different donor eyes (line no. 081309 and line no. 072810) were used. Samples were rinsed in PBS and then individually exposed to an experimental peptide in serum-free Miller medium containing 10% human complement serum (Innovative Research, catalog no. IPLA-CSER AB, lot no. L12402). The 1 μM peptide concentration employed was previously shown to be in the linear range of inhibitory concentrations during titrations. (28) One experiment employed the parent compound at 1, 10, and 50 μM. Negative control cells were exposed to Miller medium + 5% FCS; positive control cells were exposed to Miller medium + 10% human complement serum. Experimental and control solutions (1 mL) were mixed on a rocker at room temperature for 30 min, then warmed to 37 °C, before sample exposure and overnight incubation at 37 °C in a 7.0% CO₂ incubator. Following this period, the samples were rinsed with warm, sterile PBS, fixed in cold 4% paraformaldehyde (PFA) in PBS for 20 min, and stored in 0.4% PFA until use in immunohistochemical assays.

Immunohistochemistry

After rinsing the fixed samples in PBS, the inset membrane was excised with a scalpel and cut into ∼4 mm² squares. Duplicate samples from each condition were embedded in 10% agarose (Type XI, Sigma-Aldrich, catalog no. A3038) and sectioned at 100 μm using a vibratome. Sections were blocked with normal donkey serum (1/20 in PBT/PBS containing 0.5% bovine serum albumin and 0.1% Triton X-100) overnight at 4 °C. The sections were co-incubated with two primary antibodies (polyclonal goat anti-ApoE, Millipore catalog no. AB947, 1/1000 in PBT, and mouse monoclonal anti-C5b-9, Dako catalog no. MO777, 1/200 in PBT) overnight at 4 °C, then rinsed in PBT, and then co-incubated in secondary antibodies (Alexa Fluor 546-conjugated donkey anti-goat IgG and Alexa Fluor 488-conjugated donkey anti-mouse IgG, both 1/200 in PBT, Life Technologies catalog no. A-11056 and no. A-21202) overnight at 4 °C. The immunolabeled sections were then rinsed in PBT, stained with Hoechst 33342 (Life Technologies catalog no. H3570), and mounted on slides with Prolong Gold (Life Technologies catalog no. P36930).

Confocal Imaging and Analysis

Samples were imaged with an Olympus FV1000 confocal laser scanning microscope. Ten single-plane images, captured at a resolution of 1024 × 768 pixels and saved as 24-bit tiff files, were acquired for each sample. Digital image files were analyzed using MetaMorph software (Molecular Devices, Sunnyvale, CA). For image quantification, the area of C5b-9 specific fluorescence was normalized to the area of ApoE specific fluorescence and expressed as the C5b-9/ApoE ratio. Statistical significance was determined using the Mann–Whitney U test with p-value of ≤0.05 considered significant.

RP-HPLC Study

The relative lipophilicity of compstatin peptides was determined using RP-HPLC. (28, 74) This method has been used to evaluate the retention factor, k, of peptides between the hydrophobic stationary phase and hydrophilic mobile phase. The logarithm of the retention factor was determined based on the peptide retention time, t_R, and column dead time, t₀. (28) These peptides are structurally similar, some differing by only one site or position of substitution. The isocratic RP-HPLC method used in this work allows for comparison of the interaction of the structurally similar peptides with the hydrophobic stationary phase.

The separations were performed using an Agilent 1100 HPLC with UV detection at 280 nm and a Waters (Milford, MA, USA) 4.6 mm × 150 mm XTerra MS C18 column with 5 μm particles and a 125 Å pore size. The peptides were eluted using a mobile phase A, consisting of 10 mM phosphate buffer at pH of 7.4 with 1% TFA, and acetonitrile as mobile phase B. The peptides were first evaluated using method 1, running 32% B isocratically at a flow rate of 1.0 mL/min at 25 °C. The less hydrophobic peptides 3–9 and 18–20 were better resolved using isocratic method 2 which used 28% B. Triplicate 10 μL injections were performed for each peptide at concentrations ranging from 9 to 16 μM. The column dead time was determined to be 1.418 ± 0.004 (method 1) and 1.425 ± 0.006 (method 2) using a 5 mg/mL solution of aspartic acid as the unretained analyte. (28)

Dibasic sodium phosphate, aspartic acid, and acetonitrile were purchased from Fisher Scientific (Pittsburgh, PA, USA). Trifluoroacetic acid (TFA) was purchased from Acros (Geel, Belgium). HPLC-grade water was obtained from Burdick and Jackson (Muskegon, MI, USA).

Supporting Information

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Tables and figures of peptide design rankings, compstatin peptide inhibitory activity (from ELISAs, hemolytic assays, and cell based RPE assays), and solubility/lipophilicity data. This material is available free of charge via the Internet at http://pubs.acs.org.

jm501345y_si_001.pdf (235.01 kb)

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Author Information

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Corresponding Author
- Dimitrios Morikis - Department of Bioengineering, University of California, Riverside, California 92521, United States; Email: [email protected]
Authors
- Ronald D. Gorham Jr. - Department of Bioengineering, University of California, Riverside, California 92521, United States
- David L. Forest - Center for the Study of Macular Degeneration, Neuroscience Research Institute, University of California, Santa Barbara, California 93106, United States
- George A. Khoury - Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, United States
- James Smadbeck - Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, United States
- Consuelo N. Beecher - Department of Chemistry, University of California, Riverside, California 92521, United States
- Evangeline D. Healy - Center for the Study of Macular Degeneration, Neuroscience Research Institute, University of California, Santa Barbara, California 93106, United States
- Phanourios Tamamis - Department of Physics, University of Cyprus, PO20537, CY1678 Nicosia, Cyprus; Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, United States
- Georgios Archontis - Department of Physics, University of Cyprus, PO20537, CY1678 Nicosia, Cyprus
- Cynthia K. Larive - Department of Chemistry, University of California, Riverside, California 92521, United States
- Christodoulos A. Floudas - Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey 08544, United States
- Monte J. Radeke - Center for the Study of Macular Degeneration, Neuroscience Research Institute, University of California, Santa Barbara, California 93106, United States
- Lincoln V. Johnson - Center for the Study of Macular Degeneration, Neuroscience Research Institute, University of California, Santa Barbara, California 93106, United States
Notes
The authors declare the following competing financial interest(s): Dimitrios Morikis, Ronald D. Gorham, Jr., Christodoulos A. Floudas, George A. Khoury, Georgios Archontis, and Phanourios Tamamis have a patent application on the peptides reported in this paper.

Acknowledgment

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D.M. and M.J.R. acknowledge donors to Macular Degeneration Research, a program of the BrightFocus Foundation, for support of this research (Grant M2013106). D.M. is the recipient of the Carolyn K. McGillvray Memorial Award for Macular Degeneration Research, administered by the BrightFocus Foundation. D.L.F. was supported by the Garland Initiative for Vision at University of California, Santa Barbara, and the BrightFocus Foundation (Grant M2013106). C.A.F. acknowledges support from the National Institutes of Health (Grant R01GM052032). G.A.K. is grateful for support by a National Science Foundation Graduate Research Fellowship under Grant DGE-1148900. The authors gratefully acknowledge that the design calculations were performed at the TIGRESS high performance computing center at Princeton University, NJ, which is supported by the Princeton Institute for Computational Science and Engineering (PICSciE) and the Princeton University Office of Information Technology.

Abbreviations Used

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C3	complement component 3
Ac	acetyl group
C3(H₂O)	hydrolyzed C3
C3a	complement component 3a
C3b	complement component 3b
C3c	complement component 3c
C5b-9	membrane attack complex comprising complement proteins C5b, C6, C7, C8, and polymeric C9
meW	l-1-methyltryptophan
Nal	l-1-naphthylalanine
Rea	R-α-ethylalanine
Aal	R-α-allylalanine
Sea	S-α-ethylalanine
2Nl	l-2-naphthylalanine
Nmw	N-methyltryptophan
Nma	N-methylalanine
Pal	pyrenylalanine
ELISA	enzyme-linked immunosorbent assay
IC₅₀	half maximal inhibitory concentration
UV	ultraviolet
HPLC	high-performance liquid chromatography
MD	molecular dynamics
RP-HPLC	reverse phase high-performance liquid chromatography
RPE	retinal pigmented epithelium
AMD	age-related macular degeneration

References

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Morikis, Dimitrios; Assa-Munt, Nuria; Sahu, Arvind; Lambris, John D.
Protein Science (1998), 7 (3), 619-627CODEN: PRCIEI; ISSN:0961-8368. (Cambridge University Press)
The third component of complement, C3, plays a central role in activation of the classical, alternative, and lectin pathways of complement activation. Recently, we have identified a 13-residue cyclic peptide (named Compstatin) that specifically binds to C3 and inhibits complement activation. To investigate the topol. and the contribution of each crit. residue to the binding of Compstatin to C3, we have now detd. the soln. structure using 2D NMR techniques; we have also synthesized substitution analogs and used these to study the structure-function relationships involved. Finally, we have generated an ensemble of a family of soln. structures of the peptide with a hybrid distance geometry-restrained simulated-annealing methodol., using distance, dihedral angle, and 3JNH-Hα-coupling const. restraints. The Compstatin structure contained a type I β-turn comprising the segment Gln5-Asp6-Trp7-Gly8. Preference for packing of the hydrophobic side chains of Val3, Val4, and Trp7 was obsd. The generated structure was also analyzed for consistency using NMR parameters such as NOE connectivity patterns, 3JNH-Hα-coupling consts., and chem. shifts. Anal. of Ala substitution analogs suggested that Val3, Gln5, Asp6, Trp7, and Gly8 contribute significantly to the inhibitory activity of the peptide. Substitution of Gly8 caused a 100-fold decrease in inhibitory potency. In contrast, substitution of Val4, His9, His10, and Arg11 resulted in minimal change in the activity. These findings indicate that specific side-chain interactions and the β-turn are crit. for preservation of the conformational stability of Compstatin and they might be significant for maintaining the functional activity of Compstatin.
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Sahu, A.; Soulika, A. M.; Morikis, D.; Spruce, L.; Moore, W. T.; Lambris, J. D. Binding kinetics, structure-activity relationship, and biotransformation of the complement inhibitor compstatin J. Immunol. 2000, 165, 2491– 2499
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Morikis, D.; Roy, M.; Sahu, A.; Troganis, A.; Jennings, P. A.; Tsokos, G. C.; Lambris, J. D. The structural basis of compstatin activity examined by structure-function-based design of peptide analogs and NMR J. Biol. Chem. 2002, 277, 14942– 14953
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Klepeis, J. L.; Floudas, C. A.; Morikis, D.; Tsokos, C. G.; Argyropoulos, E.; Spruce, L.; Lambris, J. D. Integrated computational and experimental approach for lead optimization and design of compstatin variants with improved activity J. Am. Chem. Soc. 2003, 125, 8422– 8423
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Integrated Computational and Experimental Approach for Lead Optimization and Design of Compstatin Variants with Improved Activity
Klepeis, John L.; Floudas, Christodoulos A.; Morikis, Dimitrios; Tsokos, C. G.; Argyropoulos, E.; Spruce, L.; Lambris, John D.
Journal of the American Chemical Society (2003), 125 (28), 8422-8423CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
A novel structure-activity-based combinatorial computational optimization methodol. for the design of peptides that are candidates to become therapeutics is presented. This methodol. has been successfully applied in the design of a 7-fold more active analog, among other active analogs, in the case of the complement inhibitor compstatin. The main steps of the approach involve the availability of NMR-derived structural templates, combinatorial selection of sequences based on optimization of parametrized pairwise residue interaction potentials, prediction of fold stabilities using deterministic global optimization, and exptl. validation with immunol. activity measurements. This work is direct evidence that an integrated exptl. and theor. approach can make the engineering of compds. with enhanced immunol. properties possible.
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Soulika, A. M.; Morikis, D.; Sarrias, M.-R.; Roy, M.; Spruce, L. A.; Sahu, A.; Lambris, J. D. Studies of structure-activity relations of complement inhibitor compstatin J. Immunol. 2003, 171, 1881– 1890
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Mallik, B.; Katragadda, M.; Spruce, L. A.; Carafides, C.; Tsokos, C. G.; Morikis, D.; Lambris, J. D. Design and NMR characterization of active analogues of compstatin containing non-natural amino acids J. Med. Chem. 2005, 48, 274– 286
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Katragadda, M.; Lambris, J. D. Expression of compstatin in Escherichia coli: incorporation of unnatural amino acids enhances its activity Protein Expression Purif. 2006, 47, 289– 295
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Expression of compstatin in Escherichia coli: Incorporation of unnatural amino acids enhances its activity
Katragadda, Madan; Lambris, John D.
Protein Expression and Purification (2006), 47 (1), 289-295CODEN: PEXPEJ; ISSN:1046-5928. (Elsevier)
Compstatin, a 13-residue cyclic peptide, is a complement inhibitor that shows therapeutic potential. Several previous approaches have improved the activity of this peptide several-fold. In the present study, we have expressed and purified compstatin from Escherichia coli in an effort to increase its potency and to generate it in high yield in a more economical fashion. An intein-based expression system was used to express compstatin in fusion with chitin-binding domain and Ssp DnaB intein, which were later cleaved from the expressed mol. at room temp. and pH 7.0 to yield pure compstatin in one step. The expressed compstatin showed activity similar to the synthetic compstatin in an ELISA-based assay. The same expression system and purifn. strategy were used to incorporate three tryptophan analogs, 6-fluoro-tryptophan, 5-hydroxy-tryptophan, and 7-aza-tryptophan, into compstatin. Interestingly, incorporation of 6-fluoro-tryptophan increased the activity three-fold relative to wild-type compstatin; in contrast, incorporation of 5-hydroxy- or 7-aza-tryptophan rendered compstatin less active than the wild-type form.
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Katragadda, M.; Magotti, P.; Sfyroera, G.; Lambris, J. D. Hydrophobic effect and hydrogen bonds account for the improved activity of a complement inhibitor, compstatin J. Med. Chem. 2006, 49, 4616– 4622
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Magotti, P.; Ricklin, D.; Qu, H.; Wu, Y.-Q.; Kaznessis, Y. N.; Lambris, J. D. Structure-kinetic relationship analysis of the therapeutic complement inhibitor compstatin J. Mol. Recognit. 2009, 22, 495– 505
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Structure-kinetic relationship analysis of the therapeutic complement inhibitor compstatin
Magotti, Paola; Ricklin, Daniel; Qu, Hongchang; Wu, You-Qiang; Kaznessis, Yiannis N.; Lambris, John D.
Journal of Molecular Recognition (2009), 22 (6), 495-505CODEN: JMORE4; ISSN:0952-3499. (John Wiley & Sons Ltd.)
Compstatin is a 13-residue peptide that inhibits activation of the complement system by binding to the central component C3 and its fragments C3b and C3c. A combination of theor. and exptl. approaches has previously allowed us to develop analogs of the original compstatin peptide with up to 264-fold higher activity; one of these analogs is now in clin. trials for the treatment of age-related macular degeneration (AMD). Here we used functional assays, surface plasmon resonance (SPR), and isothermal titrn. calorimetry (ITC) to assess the effect of modifications at three key residues (Trp-4, Asp-6, Ala-9) on the affinity and activity of compstatin and its analogs, and we correlated our findings to the recently reported co-crystal structure of compstatin and C3c. The KD values for the panel of tested analogs ranged from 10-6 to 10-8 M. These differences in binding affinity could be attributed mainly to differences in dissocn. rather than assocn. rates, with a >4-fold range in kon values (2-10 × 105 M-1 s-1) and a koff variation of >35-fold (1-37 × 10-2 s-1) being obsd. The stability of the C3b-compstatin complex seemed to be highly dependent on hydrophobic effects at position 4, and even small changes at position 6 resulted in a loss of complex formation. Induction of a β-turn shift by an A9P modification resulted in a more favorable entropy but a loss of binding specificity and stability. The results obtained by the three methods utilized here were highly correlated with regard to the activity/affinity of the analogs. Thus, our analyses have identified essential structural features of compstatin and provided important information to support the development of analogs with improved efficacy. Copyright © 2009 John Wiley & Sons, Ltd.
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Bellows, M. L.; Fung, H. K.; Taylor, M. S.; Floudas, C. A.; de Victoria, A. L.; Morikis, D. New compstatin variants through two de novo protein design frameworks Biophys. J. 2010, 98, 2337– 2346
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López de Victoria, A.; Gorham, R. D.; Bellows-Peterson, M. L.; Ling, J.; Lo, D. D.; Floudas, C. A.; Morikis, D. A new generation of potent complement inhibitors of the compstatin family Chem. Biol. Drug Des. 2011, 77, 431– 440
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A new generation of potent complement inhibitors of the Compstatin family
Lopez de Victoria, Aliana; Gorham, Ronald D., Jr.; Bellows-Peterson, Meghan L.; Ling, Jun; Lo, David D.; Floudas, Christodoulos A.; Morikis, Dimitrios
Chemical Biology & Drug Design (2011), 77 (6), 431-440CODEN: CBDDAL; ISSN:1747-0277. (Wiley-Blackwell)
Compstatin family peptides are potent inhibitors of the complement system and promising drug candidates against diseases involving under-regulated complement activation. Compstatin is a 13-residue cyclized peptide that inhibits cleavage of complement protein C3, preventing downstream complement activation. We present three new compstatin variants, characterized by tryptophan replacement at positions 1 and/or 13. Peptide design was based on physicochem. reasoning and was inspired by earlier work, which identified tryptophan substitutions at positions 1 and 13 in peptides with predicted C3c binding abilities. The new variants preserve distinct polar and nonpolar surfaces of compstatin, but have altered local interaction capabilities with C3. All three peptides exhibited potent C3 binding by surface plasmon resonance and potent complement inhibition by ELISA. We also present ELISA data and detailed surface plasmon resonance kinetic data of three peptides from previous computational design.
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Qu, H.; Magotti, P.; Ricklin, D.; Wu, E. L.; Kourtzelis, I.; Wu, Y.-Q.; Kaznessis, Y. N.; Lambris, J. D. Novel analogues of the therapeutic complement inhibitor compstatin with significantly improved affinity and potency Mol. Immunol. 2011, 48, 481– 489
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Novel analogues of the therapeutic complement inhibitor compstatin with significantly improved affinity and potency
Qu Hongchang; Magotti Paola; Ricklin Daniel; Wu Emilia L; Kourtzelis Ioannis; Wu You-Qiang; Kaznessis Yiannis N; Lambris John D
Molecular immunology (2011), 48 (4), 481-9 ISSN:.
Compstatin is a 13-residue disulfide-bridged peptide that inhibits a key step in the activation of the human complement system. Compstatin and its derivatives have shown great promise for the treatment of many clinical disorders associated with unbalanced complement activity. To obtain more potent compstatin analogues, we have now performed an N-methylation scan of the peptide backbone and amino acid substitutions at position 13. One analogue (Ac-I[CVW(Me)QDW-Sar-AHRC](NMe)I-NH(2)) displayed a 1000-fold increase in both potency (IC(50) = 62 nM) and binding affinity for C3b (K(D) = 2.3 nM) over that of the original compstatin. Biophysical analysis using surface plasmon resonance and isothermal titration calorimetry suggests that the improved binding originates from more favorable free conformation and stronger hydrophobic interactions. This study provides a series of significantly improved drug leads for therapeutic applications in complement-related diseases, and offers new insights into the structure-activity relationships of compstatin analogues.
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Tamamis, P.; López de Victoria, A.; Gorham, R. D.; Bellows-Peterson, M. L.; Pierou, P.; Floudas, C. A.; Morikis, D.; Archontis, G. Molecular dynamics in drug design: new generations of compstatin analogs Chem. Biol. Drug Des. 2012, 79, 703– 718
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Molecular dynamics in drug design: new generations of compstatin analogs
Tamamis, Phanourios; Lopez de Victoria, Aliana; Gorham, Ronald D., Jr.; Bellows-Peterson, Meghan L.; Pierou, Panayiota; Floudas, Christodoulos A.; Morikis, Dimitrios; Archontis, Georgios
Chemical Biology & Drug Design (2012), 79 (5), 703-718CODEN: CBDDAL; ISSN:1747-0277. (Wiley-Blackwell)
We report the computational and rational design of new generations of potential peptide-based inhibitors of the complement protein C3 from the compstatin family. The binding efficacy of the peptides is tested by extensive mol. dynamics-based structural and physicochem. anal., using 32 at. detail trajectories in explicit water for 22 peptides bound to human, rat or mouse target protein C3, with a total of 257 ns. The criteria for the new design are: (i) optimization for C3 affinity and for the balance between hydrophobicity and polarity to improve soly. compared to known compstatin analogs; and (ii) development of dual specificity, human-rat/mouse C3 inhibitors, which could be used in animal disease models. Three of the new analogs are analyzed in more detail as they possess strong and novel binding characteristics and are promising candidates for further optimization. This work paves the way for the development of an improved therapeutic for age-related macular degeneration, and other complement system-mediated diseases, compared to known compstatin variants.
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Gorham, R. D.; Forest, D. L.; Tamamis, P.; López de Victoria, A.; Kraszni, M.; Kieslich, C. A.; Banna, C. D.; Bellows-Peterson, M. L.; Larive, C. K.; Floudas, C. A.; Archontis, G.; Johnson, L. V.; Morikis, D. Novel compstatin family peptides inhibit complement activation by drusen-like deposits in human retinal pigmented epithelial cell cultures Exp. Eye Res. 2013, 116C, 96– 108
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Qu, H.; Ricklin, D.; Bai, H.; Chen, H.; Reis, E. S.; Maciejewski, M.; Tzekou, A.; DeAngelis, R. A.; Resuello, R. R. G.; Lupu, F.; Barlow, P. N.; Lambris, J. D. New analogs of the clinical complement inhibitor compstatin with subnanomolar affinity and enhanced pharmacokinetic properties Immunobiology 2013, 218, 496– 505
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Risitano, A. M.; Ricklin, D.; Huang, Y.; Reis, E. S.; Chen, H.; Ricci, P.; Lin, Z.; Pascariello, C.; Raia, M.; Sica, M.; del Vecchio, L.; Pane, F.; Lupu, F.; Notaro, R.; Resuello, R. R. G.; Deangelis, R. A.; Lambris, J. D. Peptide inhibitors of C3 activation as a novel strategy of complement inhibition for the treatment of paroxysmal nocturnal hemoglobinuria Blood 2014, 123, 2094– 2101
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Janssen, B. J. C.; Halff, E. F.; Lambris, J. D.; Gros, P. Structure of compstatin in complex with complement component C3c reveals a new mechanism of complement inhibition J. Biol. Chem. 2007, 282, 29241– 29247
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Klepeis, J. L.; Floudas, C. A.; Morikis, D.; Tsokos, C. G.; Lambris, J. D. Design of peptide analogues with improved activity using a novel de novo protein design approach Ind. Eng. Chem. Res. 2004, 43, 3817– 3826
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Walensky, L. D.; Bird, G. H. Hydrocarbon-stapled peptides: principles, practice, and progress J. Med. Chem. 2014, 57, 6275– 6288
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Hydrocarbon-Stapled Peptides: Principles, Practice, and Progress
Walensky, Loren D.; Bird, Gregory H.
Journal of Medicinal Chemistry (2014), 57 (15), 6275-6288CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
A review. Protein structure underlies essential biol. processes and provides a blueprint for mol. mimicry that drives drug discovery. Although small mols. represent the lion's share of agents that target proteins for therapeutic benefit, there remains no substitute for the natural properties of proteins and their peptide subunits in the majority of biol. contexts. The peptide α-helix represents a common structural motif that mediates communication between signaling proteins. Because peptides can lose their shape when taken out of context, developing chem. interventions to stabilize their bioactive structure remains an active area of research. The all-hydrocarbon staple has emerged as one such soln., conferring α-helical structure, protease resistance, cellular penetrance, and biol. activity upon successful incorporation of a series of design and application principles. Here, we describe our more than decade-long experience in developing stapled peptides as biomedical research tools and prototype therapeutics, highlighting lessons learned, pitfalls to avoid, and keys to success.
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Chi, Z.-L.; Yoshida, T.; Lambris, J. D.; Iwata, T. Suppression of drusen formation by compstatin, a peptide inhibitor of complement C3 activation, on cynomolgus monkey with early-onset macular degeneration Adv. Exp. Med. Biol. 2010, 703, 127– 135
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Yehoshua, Z.; Rosenfeld, P. J.; Albini, T. A. Current clinical trials in dry AMD and the definition of appropriate clinical outcome measures Semin. Ophthalmol. 2011, 26, 167– 180
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Current Clinical Trials in Dry AMD and the Definition of Appropriate Clinical Outcome Measures
Yehoshua Zohar; Rosenfeld Philip J; Albini Thomas A
Seminars in ophthalmology (2011), 26 (3), 167-80 ISSN:.
Currently, there is no proven drug treatment for dry age-related macular degeneration (AMD). Several different treatment strategies are being investigated, including complement inhibition, neuroprotection, and visual cycle inhibitors, and novel clinical trial endpoints are being explored. Studies have identified genetic predispositions for dry AMD associated with complement dysfunction. Consequently, complement-based therapeutic treatment modalities are promising.
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Hilbich, C.; Kisters-Woike, B.; Reed, J.; Masters, C. L.; Beyreuther, K. Substitutions of hydrophobic amino acids reduce the amyloidogenicity of Alzheimer’s disease beta A4 peptides J. Mol. Biol. 1992, 228, 460– 473
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Knerr, P. J.; Tzekou, A.; Ricklin, D.; Qu, H.; Chen, H.; van der Donk, W. A.; Lambris, J. D. Synthesis and activity of thioether-containing analogues of the complement inhibitor compstatin ACS Chem. Biol. 2011, 6, 753– 760
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Smadbeck, J.; Peterson, M. B.; Khoury, G. A.; Taylor, M. S.; Floudas, C. A. Protein WISDOM: a workbench for in silico de novo design of biomolecules J. Visualized Exp. 2013, e50476– e50476
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Rajgaria, R.; McAllister, S. R.; Floudas, C. A. Distance dependent centroid to centroid force fields using high resolution decoys Proteins 2008, 70, 950– 970
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Güntert, P. Automated NMR structure calculation with CYANA Methods Mol. Biol. 2004, 278, 353– 378
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Automated NMR structure calculation with CYANA
Guntert, Peter
Methods in Molecular Biology (Totowa, NJ, United States) (2004), 278 (Protein NMR Techniques), 353-378CODEN: MMBIED; ISSN:1064-3745. (Humana Press Inc.)
This chapter gives an introduction to automated NMR structure calcn. with the program CYANA. Given a sufficiently complete list of assigned chem. shifts and one or several lists of cross-peak positions and columns from two-, three-, or four-dimensional nuclear Overhauser effect spectroscopy (NOESY) spectra, the assignment of the NOESY cross-peaks and the three-dimensional structure of the protein in soln. can be calcd. automatically with CYANA.
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Güntert, P.; Mumenthaler, C.; Wüthrich, K. Torsion angle dynamics for NMR structure calculation with the new program DYANA J. Mol. Biol. 1997, 273, 283– 298
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Torsion angle dynamics for NMR structure calculation with the new program DYANA
Guntert, P.; Mumenthaler, C.; Wuthrich, K.
Journal of Molecular Biology (1997), 273 (1), 283-298CODEN: JMOBAK; ISSN:0022-2836. (Academic)
The new program DYANA (DYnamics Algorithm for Nmr Applications) for efficient calcn. of three-dimensional protein and nucleic acid structures from distance constraints and torsion angle constraints collected by NMR expts. performs simulated annealing by mol. dynamics in torsion angle space and uses a fast recursive algorithm to integrate the equations of motions. Torsion angle dynamics can be more efficient than mol. dynamics in Cartesian coordinate space because of the reduced no. of degrees of freedom and the concomitant absence of high-frequency bond and angle vibrations, which allows for the use of longer time-steps and/or higher temps. in the structure calcn. It also represents a significant advance over the variable target function method in torsion angle space with the REDAC strategy used by the predecessor program DIANA. DYANA computation times per accepted conformer in the "bundle" used to represent the NMR structure compare favorably with those of other presently available structure calcn. algorithms, and are of the order of 160 s for a protein of 165 amino acid residues when using a DEC Alpha 8400 5/300 computer. Test calcns. starting from conformers with random torsion angle values further showed that DYANA is capable of efficient calcn. of high-quality protein structures with up to 400 amino acid residues, and of nucleic acid structures.
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Ponder, J. W. TINKER, Software Tools for Molecular Design. Jay Ponder Lab, Washington Unversity: St. Louis, MO, 2004.
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Cornell, W. D.; Cieplak, P.; Bayly, C. I.; Gould, I. R.; Merz, K. M.; Ferguson, D. M.; Spellmeyer, D. C.; Fox, T.; Caldwell, J. W.; Kollman, P. A. A second generation force field for the simulation of proteins, nucleic acids, and organic molecules J. Am. Chem. Soc. 1995, 117, 5179– 5197
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A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules
Cornell, Wendy D.; Cieplak, Piotr; Bayly, Christopher I.; Gould, Ian R.; Merz, Kenneth M., Jr.; Ferguson, David M.; Spellmeyer, David C.; Fox, Thomas; Caldwell, James W.; Kollman, Peter A.
Journal of the American Chemical Society (1995), 117 (19), 5179-97CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
The authors present the derivation of a new mol. mech. force field for simulating the structures, conformational energies, and interaction energies of proteins, nucleic acids, and many related org. mols. in condensed phases. This effective two-body force field is the successor to the Weiner et al. force field and was developed with some of the same philosophies, such as the use of a simple diagonal potential function and electrostatic potential fit atom centered charges. The need for a 10-12 function for representing hydrogen bonds is no longer necessary due to the improved performance of the new charge model and new van der Waals parameters. These new charges are detd. using a 6-31G* basis set and restrained electrostatic potential (RESP) fitting and have been shown to reproduce interaction energies, free energies of solvation, and conformational energies of simple small mols. to a good degree of accuracy. Furthermore, the new RESP charges exhibit less variability as a function of the mol. conformation used in the charge detn. The new van der Waals parameters have been derived from liq. simulations and include hydrogen parameters which take into account the effects of any geminal electroneg. atoms. The bonded parameters developed by Weiner et al. were modified as necessary to reproduce exptl. vibrational frequencies and structures. Most of the simple dihedral parameters have been retained from Weiner et al., but a complex set of .vphi. and ψ parameters which do a good job of reproducing the energies of the low-energy conformations of glycyl and alanyl dipeptides was developed for the peptide backbone.
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Lilien, R. H.; Stevens, B. W.; Anderson, A. C.; Donald, B. R. A novel ensemble-based scoring and search algorithm for protein redesign and its application to modify the substrate specificity of the gramicidin synthetase a phenylalanine adenylation enzyme J. Comput. Biol. 2005, 12, 740– 761
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A Novel Ensemble-Based Scoring and Search Algorithm for Protein Redesign and Its Application to Modify the Substrate Specificity of the Gramicidin Synthetase A Phenylalanine Adenylation Enzyme
Lilien, Ryan H.; Stevens, Brian W.; Anderson, Amy C.; Donald, Bruce R.
Journal of Computational Biology (2005), 12 (6), 740-761CODEN: JCOBEM; ISSN:1066-5277. (Mary Ann Liebert, Inc.)
Realization of novel mol. function requires the ability to alter mol. complex formation. Enzymic function can be altered by changing enzyme-substrate interactions via modification of an enzyme's active site. A redesigned enzyme may either perform a novel reaction on its native substrates or its native reaction on novel substrates. A no. of computational approaches have been developed to address the combinatorial nature of the protein redesign problem. These approaches typically search for the global min. energy conformation among an exponential no. of protein conformations. We present a novel algorithm for protein redesign, which combines a statistical mechanics-derived ensemble-based approach to computing the binding const. with the speed and completeness of a branch-and-bound pruning algorithm. In addn., we developed an efficient deterministic approxn. algorithm, capable of approximating our scoring function to arbitrary precision. In practice, the approxn. algorithm decreases the execution time of the mutation search by a factor of ten. To test our method, we examd. the Phe-specific adenylation domain of the nonribosomal peptide synthetase gramicidin synthetase A (GrsA-PheA). Ensemble scoring, using a rotameric approxn. to the partition functions of the bound and unbound states for GrsA-PheA, is first used to predict binding of the wild-type protein and a previously described mutant (selective for leucine), and second, to switch the enzyme specificity toward leucine, using two novel active site sequences computationally predicted by searching through the space of possible active site mutations. The top scoring in silico mutants were created in the wet-lab. and dissocn./binding consts. were detd. by fluorescence quenching. These tested mutations exhibit the desired change in specificity from Phe to Leu. Our ensemble-based algorithm, which flexibly models both protein and ligand using rotamer-based partition functions, has application in enzyme redesign, the prediction of protein-ligand binding, and computer-aided drug design.
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Lee, M. R.; Baker, D.; Kollman, P. A. 2.1 and 1.8 Å average Cα rmsd structure predictions on two small proteins, HP-36 and S15 J. Am. Chem. Soc. 2001, 123, 1040– 1046
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Rohl, C. A.; Baker, D. De novo determination of protein backbone structure from residual dipolar couplings using Rosetta J. Am. Chem. Soc. 2002, 124, 2723– 2729
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Rohl, C. A.; Strauss, C. E. M.; Misura, K. M. S.; Baker, D. Protein structure prediction using Rosetta. In Methods in Enzymology; Elsevier: San Diego, CA, 2004; Vol. 383, pp 66– 93.
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DiMaggio, P. A.; McAllister, S. R.; Floudas, C. A.; Feng, X.-J.; Rabinowitz, J. D.; Rabitz, H. A. Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies BMC Bioinf. 2008, 9, 458
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Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies
DiMaggio Peter A Jr; McAllister Scott R; Floudas Christodoulos A; Feng Xiao-Jiang; Rabinowitz Joshua D; Rabitz Herschel A
BMC bioinformatics (2008), 9 (), 458 ISSN:.
BACKGROUND: The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem in the analysis of gene expression data since genes may only jointly respond over a subset of conditions. Biclustering algorithms also have important applications in sample classification where, for instance, tissue samples can be classified as cancerous or normal. Many of the methods for biclustering, and clustering algorithms in general, utilize simplified models or heuristic strategies for identifying the "best" grouping of elements according to some metric and cluster definition and thus result in suboptimal clusters. RESULTS: In this article, we present a rigorous approach to biclustering, OREO, which is based on the Optimal RE-Ordering of the rows and columns of a data matrix so as to globally minimize the dissimilarity metric. The physical permutations of the rows and columns of the data matrix can be modeled as either a network flow problem or a traveling salesman problem. Cluster boundaries in one dimension are used to partition and re-order the other dimensions of the corresponding submatrices to generate biclusters. The performance of OREO is tested on (a) metabolite concentration data, (b) an image reconstruction matrix, (c) synthetic data with implanted biclusters, and gene expression data for (d) colon cancer data, (e) breast cancer data, as well as (f) yeast segregant data to validate the ability of the proposed method and compare it to existing biclustering and clustering methods. CONCLUSION: We demonstrate that this rigorous global optimization method for biclustering produces clusters with more insightful groupings of similar entities, such as genes or metabolites sharing common functions, than other clustering and biclustering algorithms and can reconstruct underlying fundamental patterns in the data for several distinct sets of data matrices arising in important biological applications.
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DiMaggio, P. A., Jr; McAllister, S. R.; Floudas, C. A.; Feng, X.-J.; Rabinowitz, J. D.; Rabitz, H. A. A network flow model for biclustering via optimal re-ordering of data matrices J. Global Optim. 2010, 47, 343– 354
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Gray, J. J.; Moughon, S.; Wang, C.; Schueler-Furman, O.; Kuhlman, B.; Rohl, C. A.; Baker, D. Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations J. Mol. Biol. 2003, 331, 281– 299
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Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations
Gray, Jeffrey J.; Moughon, Stewart; Wang, Chu; Schueler-Furman, Ora; Kuhlman, Brian; Rohl, Carol A.; Baker, David
Journal of Molecular Biology (2003), 331 (1), 281-299CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Science Ltd.)
Protein-protein docking algorithms provide a means to elucidate structural details for presently unknown complexes. Here, we present and evaluate a new method to predict protein-protein complexes from the coordinates of the unbound monomer components. The method employs a low-resoln., rigid-body, Monte Carlo search followed by simultaneous optimization of backbone displacement and side-chain conformations using Monte Carlo minimization. Up to 105 independent simulations are carried out, and the resulting "decoys" are ranked using an energy function dominated by van der Waals interactions, an implicit solvation model, and an orientation-dependent hydrogen bonding potential. Top-ranking decoys are clustered to select the final predictions. Small-perturbation studies reveal the formation of binding funnels in 42 of 54 cases using coordinates derived from the bound complexes and in 32 of 54 cases using independently detd. coordinates of one or both monomers. Exptl. binding affinities correlate with the calcd. score function and explain the predictive success or failure of many targets. Global searches using one or both unbound components predict at least 25% of the native residue-residue contacts in 28 of the 32 cases where binding funnels exist. The results suggest that the method may soon be useful for generating models of biol. important complexes from the structures of the isolated components, but they also highlight the challenges that must be met to achieve consistent and accurate prediction of protein-protein interactions.
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How large is the vol. of sequence space that is compatible with a given protein structure. Starting from random sequences, low free energy sequences were generated for 108 protein backbone structures by using a Monte Carlo optimization procedure and a free energy function based primarily on Lennard-Jones packing interactions and the Lazaridis-Karplus implicit solvation model. Remarkably, in the designed sequences 51% of the core residues and 27% of all residues were identical to the amino acids in the corresponding positions in the native sequences. The lowest free energy sequences obtained for ensembles of native-like backbone structures were also similar to the native sequence. Furthermore, both the individual residue frequencies and the covariances between pairs of positions obsd. in the very large SH3 domain family were recapitulated in core sequences designed for SH3 domain structures. Taken together, these results suggest that the vol. of sequence space optimal for a protein structure is surprisingly restricted to a region around the native sequence.
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Drew, K.; Renfrew, P. D.; Craven, T. W.; Butterfoss, G. L.; Chou, F.-C.; Lyskov, S.; Bullock, B. N.; Watkins, A.; Labonte, J. W.; Pacella, M.; Kilambi, K. P.; Leaver-Fay, A.; Kuhlman, B.; Gray, J. J.; Bradley, P.; Kirshenbaum, K.; Arora, P. S.; Das, R.; Bonneau, R. Adding diverse noncanonical backbones to Rosetta: enabling peptidomimetic design PLoS One 2013, 8, e67051
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Incorporation of noncanonical amino acids into Rosetta and use in computational protein-peptide interface design
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Noncanonical amino acids (NCAAs) can be used in a variety of protein design contexts. For example, they can be used in place of the canonical amino acids (CAAs) to improve the biophys. properties of peptides that target protein interfaces. We describe the incorporation of 114 NCAAs into the protein-modeling suite Rosetta. We describe our methods for building backbone dependent rotamer libraries and the parameterization and construction of a scoring function that can be used to score NCAA contg. peptides and proteins. We validate these addns. to Rosetta and our NCAA-rotamer libraries by showing that we can improve the binding of a calpastatin derived peptides to calpain-1 by substituting NCAAs for native amino acids using Rosetta. Rosetta (executables and source), auxiliary scripts and code, and documentation can be found at online.
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Mills, J. H.; Khare, S. D.; Bolduc, J. M.; Forouhar, F.; Mulligan, V. K.; Lew, S.; Seetharaman, J.; Tong, L.; Stoddard, B. L.; Baker, D. Computational design of an unnatural amino acid dependent metalloprotein with atomic level accuracy J. Am. Chem. Soc. 2013, 135, 13393– 13399
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Genetically encoded unnatural amino acids could facilitate the design of proteins and enzymes of novel function, but correctly specifying sites of incorporation and the identities and orientations of surrounding residues represents a formidable challenge. Computational design methods have been used to identify optimal locations for functional sites in proteins and design the surrounding residues but have not incorporated unnatural amino acids in this process. The authors extended the Rosetta design methodol. to design metalloproteins in which the amino acid (2,2'-bipyridin-5-yl)-alanine (Bpy-Ala) is a primary ligand of a bound metal ion. Following initial results that indicated the importance of buttressing the Bpy-Ala amino acid, the authors designed a buried metal binding site with octahedral coordination geometry consisting of Bpy-Ala, two protein-based metal ligands, and two metal-bound water mols. Exptl. characterization revealed a Bpy-Ala-mediated metalloprotein with the ability to bind divalent cations including Co2+, Zn2+, Fe2+, and Ni2+, with a Kd for Zn2+ of ∼40 pM. X-ray crystal structures of the designed protein bound to Co2+ and Ni2+ have RMSDs to the design model of 0.9 and 1.0 Å resp. over all atoms in the binding site.
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The structural and thermodn. properties of a 6-residue β-peptide I that was designed to form a hairpin conformation have been studied by NMR spectroscopy and mol. dynamics simulation in methanol soln. The predicted hairpin would be characterized by a 10-membered hydrogen-bonded turn involving residues 3 and 4, and two extended antiparallel strands. The interproton distances and backbone torsional dihedral angles derived from the NMR expts. at room temp. are in general terms compatible with the hairpin conformation. Two trajectories of system configurations from 100-ns mol.-dynamics simulations of the peptide in soln. at 298 and 340 K have been analyzed. In both simulations, reversible folding to the hairpin conformation is obsd. Interestingly, there is a significant conformational overlap between the unfolded state of the peptide at each of the temps. As already obsd. in previous studies of peptide folding, the unfolded state is composed of a (relatively) small no. of predominant conformers and in this case lacks any type of secondary-structure element. The trajectories provide an excellent ground for the interpretation of the NMR-derived data in terms of ensemble avs. and distributions as opposed to single-conformation interpretations. From this perspective, a relative population of the hairpin conformation of 20% to 30% would suffice to explain the NMR-derived data. Surprisingly, however, the ensemble of structures from the simulation at 340 K reproduces more accurately the NMR-derived data than the ensemble from the simulation at 298 K, and this point needs further investigation.
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The authors introduce Forcefield_PTM, a set of AMBER forcefield parameters consistent with ff03 for 32 common post-translational modifications. Partial charges were calcd. through ab initio calcns. and a two-stage RESP-fitting procedure in an ether-like implicit solvent environment. The charges are generally consistent with others previously reported for phosphorylated amino acids, and trimethyllysine, using different parametrization methods. Pairs of modified structures and their corresponding unmodified structures were curated from the PDB for both single and multiple modifications. Background structural similarity was assessed in the context of secondary and tertiary structures from the global data set. Next, the charges derived for Forcefield_PTM were tested on a macroscopic scale using unrestrained all-atom Langevin mol. dynamics simulations in AMBER for 34 (17 pairs of modified/unmodified) systems in implicit solvent. Assessment was performed in the context of secondary structure preservation, stability in energies, and correlations between the modified and unmodified structure trajectories on the aggregate. As an illustration of their utility, the parameters were used to compare the structural stability of the phosphorylated and dephosphorylated forms of OdhI. Microscopic comparisons between quantum and AMBER single point energies along key χ torsions on several PTMs were performed, and corrections to improve their agreement in terms of mean-squared errors and squared correlation coeffs. were parametrized. This forcefield for post-translational modifications in condensed-phase simulations can be applied to a no. of biol. relevant and timely applications including protein structure prediction, protein and peptide design, and docking and to study the effect of PTMs on folding and dynamics. The authors make the derived parameters and an assocd. interactive webtool capable of performing post-translational modifications on proteins using Forcefield_PTM available at http://selene.princeton.edu/FFPTM.
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Abstract
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Figure 1
Figure 1. Chemical structures of non-natural amino acids in compstatin peptide sequences. The abbreviations used in sequences (Table 1) are shown in parentheses.
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Figure 2
Figure 2. Concentration-dependent inhibition curves of compstatin peptides in C3b and C5b-9 ELISAs and hemolytic assays. Data show C3b, C5b-9, and hemolysis inhibition (from left to right) for set 1 (A–C), set 2 (D–F), set 3 (G–I), set 4 (J–L), set 5 (M–O), and control (P–R) peptides. Data points indicate mean percent inhibition ± SEM (standard error of the mean). The intersection of dashed lines shows the IC₅₀ value for meW4A9 in all plots. Curves to the right and left of the intersection point represent peptides with higher IC₅₀ values and lower IC₅₀ values compared to meW4A9, respectively.
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Figure 3
Figure 3. IC₅₀ values for compstatin peptides. Bar plots show IC₅₀ values for compstatin peptides 1–20 and positive control peptides W4A9, meW4A9, and Parent in C3b ELISA (A), C5b-9 ELISA (B), and hemolytic assay (C). Bars show mean IC₅₀ from three independent runs of each experiment (±95% confidence interval). The dashed horizontal line shows the IC₅₀ value for the meW4A9 control peptide, for ease of comparison.
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Figure 4
Figure 4. Effects of compstatin peptides on complement activation in the RPE cell in vitro assay. The ratio of C5b-9/ApoE fluorescence (±SEM, n = 10) is plotted as a percentage of the positive control (POS) for two hfRPE cell lines, 072810 (gray) and 081309 (black). Untreated cells that were not incubated with complement-competent human serum served as negative control (NEG). At 1 μM, the parent compound is not significantly different from the positive or linear peptide controls. All test peptides (W4A9, PEP 5, PEP 8, PEP 12, PEP 18, and PEP 19) displayed significant complement inhibition relative to their corresponding positive control (see Tables S5 and S6).
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Figure 5
Figure 5. Effects of varying concentrations of Parent on complement activation in the RPE cell in vitro assay. The ratio of C5b-9/ApoE fluorescence (±SEM, n = 10) is plotted as a percentage of the positive control. Parent was tested at concentrations of 1, 10, and 50 μM (PAR1, PAR10, and PAR50). The concentration of W4A9 was 1 μM. All values are expressed relative to the positive control. Parent shows no significant difference from the positive control at 1 μM or 10 μM concentrations. At 50 μM the effect of Parent is equivalent to that of 1 μM W4A9. Both Parent at 50 μM and W4A9 at 1 μM are significantly different than the positive control (p-value of <0.001, two-tailed Mann–Whitney U test).
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Figure 6
Figure 6. Relation between activity and solubility of compstatin peptides. IC₅₀ values for compstatin peptides in C3b ELISA (A), C5b-9 ELISA (B), and hemolytic assay (C) are plotted against solubility. Horizontal and vertical error bars represent the standard deviation and 95% confidence intervals of solubility and IC₅₀, respectively. Points inside the ellipse (lower right corner) have a favorable balance between activity and solubility. Note the peptide 8 solubility was measured using less starting material compared to the rest, and thus, its solubility is not directly comparable to that of other peptides.
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Figure 7
Figure 7. RP-HPLC retention factors for compstatin peptides. Bar plots show log(k) values for compstatin peptides 1–20 and positive control peptides W4A9, meW4A9, and Parent in C3b ELISA. The dashed horizontal line shows the log(k) value for the meW4A9 control peptide, for ease of comparison.
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References
This article references 74 other publications.
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  Walport, M. J. Complement. Second of two parts N. Engl. J. Med. 2001, 344, 1140– 1144
  1
  Complement in immune responses
  Walport, Mark J.
  New England Journal of Medicine (2001), 344 (15), 1140-1144CODEN: NEJMAG; ISSN:0028-4793. (Massachusetts Medical Society)
  A review with 96 refs. focusing on the complement system. Topics discussed include the complement at the interface between innate and adaptive immunity; the link between the complement and inflammation; the assocn. between the complement and necrosis; the relationship between the complement and immune complexes; the role of complement deficiency in systemic lupus erythematosus; and the hypothesis that the failure of the complement to dispose of the remnants of apoptotic cells may evoke an autoimmune response.
2. 2
  Ricklin, D.; Lambris, J. D. Complement-targeted therapeutics Nat. Biotechnol. 2007, 25, 1265– 1275
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3. 3
  Ricklin, D.; Lambris, J. D. Complement in immune and inflammatory disorders: therapeutic interventions J. Immunol. 2013, 190, 3839– 3847
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4. 4
  Qu, H.; Ricklin, D.; Lambris, J. D. Recent developments in low molecular weight complement inhibitors Mol. Immunol. 2009, 47, 185– 195
  4
  Recent developments in low molecular weight complement inhibitors
  Qu, Hongchang; Ricklin, Daniel; Lambris, John D.
  Molecular Immunology (2009), 47 (2-3), 185-195CODEN: MOIMD5; ISSN:0161-5890. (Elsevier Ltd.)
  A review. As a key part of the innate immune system, complement plays an important role not only in defending against invading pathogens but also in many other biol. processes. Inappropriate or excessive activation of complement has been linked to many autoimmune, inflammatory, and neurodegenerative diseases, as well as ischemia-reperfusion injury and cancer. A wide array of low mol. wt. complement inhibitors has been developed to target various components of the complement cascade. Their efficacy has been demonstrated in numerous in vitro and in vivo expts. Though none of these inhibitors has reached the market so far, some of them have entered clin. trials and displayed promising results. This review provides a brief overview of the currently developed low mol. wt. complement inhibitors, including short peptides and synthetic small mols., with an emphasis on those targeting components C1 and C3, and the anaphylatoxin receptors.
5. 5
  Sahu, A.; Kay, B. Inhibition of human complement by a C3-binding peptide isolated from a phage-displayed random peptide library J. Immunol. 1996, 157, 884– 891
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6. 6
  Morikis, D.; Sahu, A.; Moore, W. T.; Lambris, J. D. Design, structure, function and application of compstatin. In Bioactive Peptides in Drug Discovery and Design: Medical Aspects; Matsoukas, J.; Mavromoustakos, T., Eds.; IOS Press: Amsterdam, The Netherlands, 1999; pp 235– 246.
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7. 7
  Sahu, A.; Morikis, D.; Lambris, J. D. Complement inhibitors targeting C3, C4, and C5. In Therapeutic Interventions in the Complement System; Lambris, J. D.; Holers, V. M., Eds.; Humana Press: Totowa, NJ, U.S., 2000; pp 75– 112.
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8. 8
  Morikis, D.; Lambris, J. D. Structural aspects and design of low-molecular-mass complement inhibitors Biochem. Soc. Trans. 2002, 30, 1026– 1036
  8
  Structural aspects and design of low-molecular-mass complement inhibitors
  Morikis, D.; Lambris, J. D.
  Biochemical Society Transactions (2002), 30 (6), 1026-1036CODEN: BCSTB5; ISSN:0300-5127. (Portland Press Ltd.)
  A review. We present a mini-review on the structure-based design of three promising complement inhibitors. Firstly, we review compstatin, a 13-residue cyclic peptide that binds to C3 and inhibits the cleavage of C3 to C3a and C3b. Secondly, we review a six-residue cyclic peptide that binds to C5aR and antagonizes the binding of C5a to its receptor C5aR. Finally, we review three small mols. that bind to Factor D and inhibit the enzymic action of Factor D, during which Factor D proteolytically cleaves Factor B in complex with C3 or C3b.
9. 9
  Morikis, D.; Soulika, A. M.; Mallik, B.; Klepeis, J. L.; Floudas, C. A.; Lambris, J. D. Improvement of the anti-C3 activity of compstatin using rational and combinatorial approaches Biochem. Soc. Trans. 2004, 32, 28– 32
  9
  Improvement of the anti-C3 activity of compstatin using rational and combinatorial approaches
  Morikis, D.; Soulika, A. M.; Mallik, B.; Klepeis, J. L.; Floudas, C. A.; Lambris, J. D.
  Biochemical Society Transactions (2004), 32 (1), 28-32CODEN: BCSTB5; ISSN:0300-5127. (Portland Press Ltd.)
  A review. Compstatin is a 13-residue cyclic peptide that has the ability to inhibit the cleavage of C3 to C3a and C3b. The effects of targeting C3 cleavage are threefold, and result in hindrance of: (i) the generation of the pro-inflammatory peptide C3a, (ii) the generation of opsonin C3b (or its fragment C3d), and (iii) further complement activation of the common pathway (beyond C3) with the end result of the generation of the membrane attack complex. We will report on our progress on: (i) rational design of more active compstatin analogs based on the three-dimensional structure of compstatin, (ii) exptl. combinatorial design based on the generation of a phage-displayed peptide library partially randomized with the implementation of structure-induced restraints, and (iii) theor. combinatorial design based on a novel computational optimization method, structure-induced restraints and flexible structural templates. All three approaches have resulted in analogs with improved activities. Currently, the lead analog has the sequence acetyl-I[CVYQDWGAHRC]T-NH2 (where the brackets denote cyclization), and is 16-fold more active than the parent peptide. We will also report on our progress towards understanding the dynamic character of compstatin using mol. dynamics simulations. The identification of an ensemble of interconverting conformers of compstatin with variable populations is a first step towards the incorporation of dynamic elements in the design of new analogs using dynamics-activity relationships in addn. to structure-activity relationships.
10. 10
  Holland, M. C. H.; Morikis, D.; Lambris, J. D. Synthetic small-molecule complement inhibitors Curr. Opin. Invest. Drugs 2004, 5, 1164– 1173
  There is no corresponding record for this reference.
11. 11
  Floudas, C.; Klepeis, J.; Lambris, J. D.; Morikis, D. De novo protein design: an interplay of global optimization, mixed-integer optimization and experiments. In FOCAPD 2004, Sixth International Conference on Foundations of Computer-Aided Process Design, Discovery through Product and Process Design; Floudas, C. A.; Agrawal, R., Eds.; CACHE Corporation: Austin, TX, U.S., 2004; pp 133– 146.
  There is no corresponding record for this reference.
12. 12
  Morikis, D.; Floudas, C.; Lambris, J. D. Structure-based integrative computational and experimental approach for the optimization of drug design. In ICCS 2005, Lecture Notes in Computer Science: Computational Science; Sunderam, V. S.; van Albada, G. D.; Sloot, P. M.; Dongarra, J., Eds.; Springer-Verlag: Berlin, Germany, 2005; pp 680– 688.
  There is no corresponding record for this reference.
13. 13
  Morikis, D.; Lambris, J. D. Structure, dynamics, activity, and function of compstatin and design of more potent analogs. In Structural Biology of the Complement System; Morikis, D.; Lambris, J. D., Eds.; CRC Press: Boca Raton, FL, U.S., 2005; pp 317– 340.
  There is no corresponding record for this reference.
14. 14
  Ricklin, D.; Lambris, J. D. Compstatin: a complement inhibitor on its way to clinical application. In Current Topics in Complement II: Advances in Experimental Medicine and Biology; Springer US: New York, NY, U.S., 2008; pp 262– 281.
  There is no corresponding record for this reference.
15. 15
  Morikis, D.; Assa-Munt, N.; Sahu, A.; Lambris, J. D. Solution structure of compstatin, a potent complement inhibitor Protein Sci. 1998, 7, 619– 627
  15
  Solution structure of Compstatin, a potent complement inhibitor
  Morikis, Dimitrios; Assa-Munt, Nuria; Sahu, Arvind; Lambris, John D.
  Protein Science (1998), 7 (3), 619-627CODEN: PRCIEI; ISSN:0961-8368. (Cambridge University Press)
  The third component of complement, C3, plays a central role in activation of the classical, alternative, and lectin pathways of complement activation. Recently, we have identified a 13-residue cyclic peptide (named Compstatin) that specifically binds to C3 and inhibits complement activation. To investigate the topol. and the contribution of each crit. residue to the binding of Compstatin to C3, we have now detd. the soln. structure using 2D NMR techniques; we have also synthesized substitution analogs and used these to study the structure-function relationships involved. Finally, we have generated an ensemble of a family of soln. structures of the peptide with a hybrid distance geometry-restrained simulated-annealing methodol., using distance, dihedral angle, and 3JNH-Hα-coupling const. restraints. The Compstatin structure contained a type I β-turn comprising the segment Gln5-Asp6-Trp7-Gly8. Preference for packing of the hydrophobic side chains of Val3, Val4, and Trp7 was obsd. The generated structure was also analyzed for consistency using NMR parameters such as NOE connectivity patterns, 3JNH-Hα-coupling consts., and chem. shifts. Anal. of Ala substitution analogs suggested that Val3, Gln5, Asp6, Trp7, and Gly8 contribute significantly to the inhibitory activity of the peptide. Substitution of Gly8 caused a 100-fold decrease in inhibitory potency. In contrast, substitution of Val4, His9, His10, and Arg11 resulted in minimal change in the activity. These findings indicate that specific side-chain interactions and the β-turn are crit. for preservation of the conformational stability of Compstatin and they might be significant for maintaining the functional activity of Compstatin.
16. 16
  Sahu, A.; Soulika, A. M.; Morikis, D.; Spruce, L.; Moore, W. T.; Lambris, J. D. Binding kinetics, structure-activity relationship, and biotransformation of the complement inhibitor compstatin J. Immunol. 2000, 165, 2491– 2499
  There is no corresponding record for this reference.
17. 17
  Morikis, D.; Roy, M.; Sahu, A.; Troganis, A.; Jennings, P. A.; Tsokos, G. C.; Lambris, J. D. The structural basis of compstatin activity examined by structure-function-based design of peptide analogs and NMR J. Biol. Chem. 2002, 277, 14942– 14953
  There is no corresponding record for this reference.
18. 18
  Klepeis, J. L.; Floudas, C. A.; Morikis, D.; Tsokos, C. G.; Argyropoulos, E.; Spruce, L.; Lambris, J. D. Integrated computational and experimental approach for lead optimization and design of compstatin variants with improved activity J. Am. Chem. Soc. 2003, 125, 8422– 8423
  18
  Integrated Computational and Experimental Approach for Lead Optimization and Design of Compstatin Variants with Improved Activity
  Klepeis, John L.; Floudas, Christodoulos A.; Morikis, Dimitrios; Tsokos, C. G.; Argyropoulos, E.; Spruce, L.; Lambris, John D.
  Journal of the American Chemical Society (2003), 125 (28), 8422-8423CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
  A novel structure-activity-based combinatorial computational optimization methodol. for the design of peptides that are candidates to become therapeutics is presented. This methodol. has been successfully applied in the design of a 7-fold more active analog, among other active analogs, in the case of the complement inhibitor compstatin. The main steps of the approach involve the availability of NMR-derived structural templates, combinatorial selection of sequences based on optimization of parametrized pairwise residue interaction potentials, prediction of fold stabilities using deterministic global optimization, and exptl. validation with immunol. activity measurements. This work is direct evidence that an integrated exptl. and theor. approach can make the engineering of compds. with enhanced immunol. properties possible.
19. 19
  Soulika, A. M.; Morikis, D.; Sarrias, M.-R.; Roy, M.; Spruce, L. A.; Sahu, A.; Lambris, J. D. Studies of structure-activity relations of complement inhibitor compstatin J. Immunol. 2003, 171, 1881– 1890
  There is no corresponding record for this reference.
20. 20
  Mallik, B.; Katragadda, M.; Spruce, L. A.; Carafides, C.; Tsokos, C. G.; Morikis, D.; Lambris, J. D. Design and NMR characterization of active analogues of compstatin containing non-natural amino acids J. Med. Chem. 2005, 48, 274– 286
  There is no corresponding record for this reference.
21. 21
  Katragadda, M.; Lambris, J. D. Expression of compstatin in Escherichia coli: incorporation of unnatural amino acids enhances its activity Protein Expression Purif. 2006, 47, 289– 295
  21
  Expression of compstatin in Escherichia coli: Incorporation of unnatural amino acids enhances its activity
  Katragadda, Madan; Lambris, John D.
  Protein Expression and Purification (2006), 47 (1), 289-295CODEN: PEXPEJ; ISSN:1046-5928. (Elsevier)
  Compstatin, a 13-residue cyclic peptide, is a complement inhibitor that shows therapeutic potential. Several previous approaches have improved the activity of this peptide several-fold. In the present study, we have expressed and purified compstatin from Escherichia coli in an effort to increase its potency and to generate it in high yield in a more economical fashion. An intein-based expression system was used to express compstatin in fusion with chitin-binding domain and Ssp DnaB intein, which were later cleaved from the expressed mol. at room temp. and pH 7.0 to yield pure compstatin in one step. The expressed compstatin showed activity similar to the synthetic compstatin in an ELISA-based assay. The same expression system and purifn. strategy were used to incorporate three tryptophan analogs, 6-fluoro-tryptophan, 5-hydroxy-tryptophan, and 7-aza-tryptophan, into compstatin. Interestingly, incorporation of 6-fluoro-tryptophan increased the activity three-fold relative to wild-type compstatin; in contrast, incorporation of 5-hydroxy- or 7-aza-tryptophan rendered compstatin less active than the wild-type form.
22. 22
  Katragadda, M.; Magotti, P.; Sfyroera, G.; Lambris, J. D. Hydrophobic effect and hydrogen bonds account for the improved activity of a complement inhibitor, compstatin J. Med. Chem. 2006, 49, 4616– 4622
  There is no corresponding record for this reference.
23. 23
  Magotti, P.; Ricklin, D.; Qu, H.; Wu, Y.-Q.; Kaznessis, Y. N.; Lambris, J. D. Structure-kinetic relationship analysis of the therapeutic complement inhibitor compstatin J. Mol. Recognit. 2009, 22, 495– 505
  23
  Structure-kinetic relationship analysis of the therapeutic complement inhibitor compstatin
  Magotti, Paola; Ricklin, Daniel; Qu, Hongchang; Wu, You-Qiang; Kaznessis, Yiannis N.; Lambris, John D.
  Journal of Molecular Recognition (2009), 22 (6), 495-505CODEN: JMORE4; ISSN:0952-3499. (John Wiley & Sons Ltd.)
  Compstatin is a 13-residue peptide that inhibits activation of the complement system by binding to the central component C3 and its fragments C3b and C3c. A combination of theor. and exptl. approaches has previously allowed us to develop analogs of the original compstatin peptide with up to 264-fold higher activity; one of these analogs is now in clin. trials for the treatment of age-related macular degeneration (AMD). Here we used functional assays, surface plasmon resonance (SPR), and isothermal titrn. calorimetry (ITC) to assess the effect of modifications at three key residues (Trp-4, Asp-6, Ala-9) on the affinity and activity of compstatin and its analogs, and we correlated our findings to the recently reported co-crystal structure of compstatin and C3c. The KD values for the panel of tested analogs ranged from 10-6 to 10-8 M. These differences in binding affinity could be attributed mainly to differences in dissocn. rather than assocn. rates, with a >4-fold range in kon values (2-10 × 105 M-1 s-1) and a koff variation of >35-fold (1-37 × 10-2 s-1) being obsd. The stability of the C3b-compstatin complex seemed to be highly dependent on hydrophobic effects at position 4, and even small changes at position 6 resulted in a loss of complex formation. Induction of a β-turn shift by an A9P modification resulted in a more favorable entropy but a loss of binding specificity and stability. The results obtained by the three methods utilized here were highly correlated with regard to the activity/affinity of the analogs. Thus, our analyses have identified essential structural features of compstatin and provided important information to support the development of analogs with improved efficacy. Copyright © 2009 John Wiley & Sons, Ltd.
24. 24
  Bellows, M. L.; Fung, H. K.; Taylor, M. S.; Floudas, C. A.; de Victoria, A. L.; Morikis, D. New compstatin variants through two de novo protein design frameworks Biophys. J. 2010, 98, 2337– 2346
  There is no corresponding record for this reference.
25. 25
  López de Victoria, A.; Gorham, R. D.; Bellows-Peterson, M. L.; Ling, J.; Lo, D. D.; Floudas, C. A.; Morikis, D. A new generation of potent complement inhibitors of the compstatin family Chem. Biol. Drug Des. 2011, 77, 431– 440
  25
  A new generation of potent complement inhibitors of the Compstatin family
  Lopez de Victoria, Aliana; Gorham, Ronald D., Jr.; Bellows-Peterson, Meghan L.; Ling, Jun; Lo, David D.; Floudas, Christodoulos A.; Morikis, Dimitrios
  Chemical Biology & Drug Design (2011), 77 (6), 431-440CODEN: CBDDAL; ISSN:1747-0277. (Wiley-Blackwell)
  Compstatin family peptides are potent inhibitors of the complement system and promising drug candidates against diseases involving under-regulated complement activation. Compstatin is a 13-residue cyclized peptide that inhibits cleavage of complement protein C3, preventing downstream complement activation. We present three new compstatin variants, characterized by tryptophan replacement at positions 1 and/or 13. Peptide design was based on physicochem. reasoning and was inspired by earlier work, which identified tryptophan substitutions at positions 1 and 13 in peptides with predicted C3c binding abilities. The new variants preserve distinct polar and nonpolar surfaces of compstatin, but have altered local interaction capabilities with C3. All three peptides exhibited potent C3 binding by surface plasmon resonance and potent complement inhibition by ELISA. We also present ELISA data and detailed surface plasmon resonance kinetic data of three peptides from previous computational design.
26. 26
  Qu, H.; Magotti, P.; Ricklin, D.; Wu, E. L.; Kourtzelis, I.; Wu, Y.-Q.; Kaznessis, Y. N.; Lambris, J. D. Novel analogues of the therapeutic complement inhibitor compstatin with significantly improved affinity and potency Mol. Immunol. 2011, 48, 481– 489
  26
  Novel analogues of the therapeutic complement inhibitor compstatin with significantly improved affinity and potency
  Qu Hongchang; Magotti Paola; Ricklin Daniel; Wu Emilia L; Kourtzelis Ioannis; Wu You-Qiang; Kaznessis Yiannis N; Lambris John D
  Molecular immunology (2011), 48 (4), 481-9 ISSN:.
  Compstatin is a 13-residue disulfide-bridged peptide that inhibits a key step in the activation of the human complement system. Compstatin and its derivatives have shown great promise for the treatment of many clinical disorders associated with unbalanced complement activity. To obtain more potent compstatin analogues, we have now performed an N-methylation scan of the peptide backbone and amino acid substitutions at position 13. One analogue (Ac-I[CVW(Me)QDW-Sar-AHRC](NMe)I-NH(2)) displayed a 1000-fold increase in both potency (IC(50) = 62 nM) and binding affinity for C3b (K(D) = 2.3 nM) over that of the original compstatin. Biophysical analysis using surface plasmon resonance and isothermal titration calorimetry suggests that the improved binding originates from more favorable free conformation and stronger hydrophobic interactions. This study provides a series of significantly improved drug leads for therapeutic applications in complement-related diseases, and offers new insights into the structure-activity relationships of compstatin analogues.
27. 27
  Tamamis, P.; López de Victoria, A.; Gorham, R. D.; Bellows-Peterson, M. L.; Pierou, P.; Floudas, C. A.; Morikis, D.; Archontis, G. Molecular dynamics in drug design: new generations of compstatin analogs Chem. Biol. Drug Des. 2012, 79, 703– 718
  27
  Molecular dynamics in drug design: new generations of compstatin analogs
  Tamamis, Phanourios; Lopez de Victoria, Aliana; Gorham, Ronald D., Jr.; Bellows-Peterson, Meghan L.; Pierou, Panayiota; Floudas, Christodoulos A.; Morikis, Dimitrios; Archontis, Georgios
  Chemical Biology & Drug Design (2012), 79 (5), 703-718CODEN: CBDDAL; ISSN:1747-0277. (Wiley-Blackwell)
  We report the computational and rational design of new generations of potential peptide-based inhibitors of the complement protein C3 from the compstatin family. The binding efficacy of the peptides is tested by extensive mol. dynamics-based structural and physicochem. anal., using 32 at. detail trajectories in explicit water for 22 peptides bound to human, rat or mouse target protein C3, with a total of 257 ns. The criteria for the new design are: (i) optimization for C3 affinity and for the balance between hydrophobicity and polarity to improve soly. compared to known compstatin analogs; and (ii) development of dual specificity, human-rat/mouse C3 inhibitors, which could be used in animal disease models. Three of the new analogs are analyzed in more detail as they possess strong and novel binding characteristics and are promising candidates for further optimization. This work paves the way for the development of an improved therapeutic for age-related macular degeneration, and other complement system-mediated diseases, compared to known compstatin variants.
28. 28
  Gorham, R. D.; Forest, D. L.; Tamamis, P.; López de Victoria, A.; Kraszni, M.; Kieslich, C. A.; Banna, C. D.; Bellows-Peterson, M. L.; Larive, C. K.; Floudas, C. A.; Archontis, G.; Johnson, L. V.; Morikis, D. Novel compstatin family peptides inhibit complement activation by drusen-like deposits in human retinal pigmented epithelial cell cultures Exp. Eye Res. 2013, 116C, 96– 108
  There is no corresponding record for this reference.
29. 29
  Qu, H.; Ricklin, D.; Bai, H.; Chen, H.; Reis, E. S.; Maciejewski, M.; Tzekou, A.; DeAngelis, R. A.; Resuello, R. R. G.; Lupu, F.; Barlow, P. N.; Lambris, J. D. New analogs of the clinical complement inhibitor compstatin with subnanomolar affinity and enhanced pharmacokinetic properties Immunobiology 2013, 218, 496– 505
  There is no corresponding record for this reference.
30. 30
  Risitano, A. M.; Ricklin, D.; Huang, Y.; Reis, E. S.; Chen, H.; Ricci, P.; Lin, Z.; Pascariello, C.; Raia, M.; Sica, M.; del Vecchio, L.; Pane, F.; Lupu, F.; Notaro, R.; Resuello, R. R. G.; Deangelis, R. A.; Lambris, J. D. Peptide inhibitors of C3 activation as a novel strategy of complement inhibition for the treatment of paroxysmal nocturnal hemoglobinuria Blood 2014, 123, 2094– 2101
  There is no corresponding record for this reference.
31. 31
  Janssen, B. J. C.; Halff, E. F.; Lambris, J. D.; Gros, P. Structure of compstatin in complex with complement component C3c reveals a new mechanism of complement inhibition J. Biol. Chem. 2007, 282, 29241– 29247
  There is no corresponding record for this reference.
32. 32
  Klepeis, J. L.; Floudas, C. A.; Morikis, D.; Tsokos, C. G.; Lambris, J. D. Design of peptide analogues with improved activity using a novel de novo protein design approach Ind. Eng. Chem. Res. 2004, 43, 3817– 3826
  There is no corresponding record for this reference.
33. 33
  Walensky, L. D.; Bird, G. H. Hydrocarbon-stapled peptides: principles, practice, and progress J. Med. Chem. 2014, 57, 6275– 6288
  33
  Hydrocarbon-Stapled Peptides: Principles, Practice, and Progress
  Walensky, Loren D.; Bird, Gregory H.
  Journal of Medicinal Chemistry (2014), 57 (15), 6275-6288CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
  A review. Protein structure underlies essential biol. processes and provides a blueprint for mol. mimicry that drives drug discovery. Although small mols. represent the lion's share of agents that target proteins for therapeutic benefit, there remains no substitute for the natural properties of proteins and their peptide subunits in the majority of biol. contexts. The peptide α-helix represents a common structural motif that mediates communication between signaling proteins. Because peptides can lose their shape when taken out of context, developing chem. interventions to stabilize their bioactive structure remains an active area of research. The all-hydrocarbon staple has emerged as one such soln., conferring α-helical structure, protease resistance, cellular penetrance, and biol. activity upon successful incorporation of a series of design and application principles. Here, we describe our more than decade-long experience in developing stapled peptides as biomedical research tools and prototype therapeutics, highlighting lessons learned, pitfalls to avoid, and keys to success.
34. 34
  Chi, Z.-L.; Yoshida, T.; Lambris, J. D.; Iwata, T. Suppression of drusen formation by compstatin, a peptide inhibitor of complement C3 activation, on cynomolgus monkey with early-onset macular degeneration Adv. Exp. Med. Biol. 2010, 703, 127– 135
  There is no corresponding record for this reference.
35. 35
  Yehoshua, Z.; Rosenfeld, P. J.; Albini, T. A. Current clinical trials in dry AMD and the definition of appropriate clinical outcome measures Semin. Ophthalmol. 2011, 26, 167– 180
  35
  Current Clinical Trials in Dry AMD and the Definition of Appropriate Clinical Outcome Measures
  Yehoshua Zohar; Rosenfeld Philip J; Albini Thomas A
  Seminars in ophthalmology (2011), 26 (3), 167-80 ISSN:.
  Currently, there is no proven drug treatment for dry age-related macular degeneration (AMD). Several different treatment strategies are being investigated, including complement inhibition, neuroprotection, and visual cycle inhibitors, and novel clinical trial endpoints are being explored. Studies have identified genetic predispositions for dry AMD associated with complement dysfunction. Consequently, complement-based therapeutic treatment modalities are promising.
36. 36
  Hilbich, C.; Kisters-Woike, B.; Reed, J.; Masters, C. L.; Beyreuther, K. Substitutions of hydrophobic amino acids reduce the amyloidogenicity of Alzheimer’s disease beta A4 peptides J. Mol. Biol. 1992, 228, 460– 473
  There is no corresponding record for this reference.
37. 37
  Knerr, P. J.; Tzekou, A.; Ricklin, D.; Qu, H.; Chen, H.; van der Donk, W. A.; Lambris, J. D. Synthesis and activity of thioether-containing analogues of the complement inhibitor compstatin ACS Chem. Biol. 2011, 6, 753– 760
  There is no corresponding record for this reference.
38. 38
  Smadbeck, J.; Peterson, M. B.; Khoury, G. A.; Taylor, M. S.; Floudas, C. A. Protein WISDOM: a workbench for in silico de novo design of biomolecules J. Visualized Exp. 2013, e50476– e50476
  There is no corresponding record for this reference.
39. 39
  Rajgaria, R.; McAllister, S. R.; Floudas, C. A. Distance dependent centroid to centroid force fields using high resolution decoys Proteins 2008, 70, 950– 970
  There is no corresponding record for this reference.
40. 40
  Güntert, P. Automated NMR structure calculation with CYANA Methods Mol. Biol. 2004, 278, 353– 378
  40
  Automated NMR structure calculation with CYANA
  Guntert, Peter
  Methods in Molecular Biology (Totowa, NJ, United States) (2004), 278 (Protein NMR Techniques), 353-378CODEN: MMBIED; ISSN:1064-3745. (Humana Press Inc.)
  This chapter gives an introduction to automated NMR structure calcn. with the program CYANA. Given a sufficiently complete list of assigned chem. shifts and one or several lists of cross-peak positions and columns from two-, three-, or four-dimensional nuclear Overhauser effect spectroscopy (NOESY) spectra, the assignment of the NOESY cross-peaks and the three-dimensional structure of the protein in soln. can be calcd. automatically with CYANA.
41. 41
  Güntert, P.; Mumenthaler, C.; Wüthrich, K. Torsion angle dynamics for NMR structure calculation with the new program DYANA J. Mol. Biol. 1997, 273, 283– 298
  41
  Torsion angle dynamics for NMR structure calculation with the new program DYANA
  Guntert, P.; Mumenthaler, C.; Wuthrich, K.
  Journal of Molecular Biology (1997), 273 (1), 283-298CODEN: JMOBAK; ISSN:0022-2836. (Academic)
  The new program DYANA (DYnamics Algorithm for Nmr Applications) for efficient calcn. of three-dimensional protein and nucleic acid structures from distance constraints and torsion angle constraints collected by NMR expts. performs simulated annealing by mol. dynamics in torsion angle space and uses a fast recursive algorithm to integrate the equations of motions. Torsion angle dynamics can be more efficient than mol. dynamics in Cartesian coordinate space because of the reduced no. of degrees of freedom and the concomitant absence of high-frequency bond and angle vibrations, which allows for the use of longer time-steps and/or higher temps. in the structure calcn. It also represents a significant advance over the variable target function method in torsion angle space with the REDAC strategy used by the predecessor program DIANA. DYANA computation times per accepted conformer in the "bundle" used to represent the NMR structure compare favorably with those of other presently available structure calcn. algorithms, and are of the order of 160 s for a protein of 165 amino acid residues when using a DEC Alpha 8400 5/300 computer. Test calcns. starting from conformers with random torsion angle values further showed that DYANA is capable of efficient calcn. of high-quality protein structures with up to 400 amino acid residues, and of nucleic acid structures.
42. 42
  Ponder, J. W. TINKER, Software Tools for Molecular Design. Jay Ponder Lab, Washington Unversity: St. Louis, MO, 2004.
  There is no corresponding record for this reference.
43. 43
  Cornell, W. D.; Cieplak, P.; Bayly, C. I.; Gould, I. R.; Merz, K. M.; Ferguson, D. M.; Spellmeyer, D. C.; Fox, T.; Caldwell, J. W.; Kollman, P. A. A second generation force field for the simulation of proteins, nucleic acids, and organic molecules J. Am. Chem. Soc. 1995, 117, 5179– 5197
  43
  A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules
  Cornell, Wendy D.; Cieplak, Piotr; Bayly, Christopher I.; Gould, Ian R.; Merz, Kenneth M., Jr.; Ferguson, David M.; Spellmeyer, David C.; Fox, Thomas; Caldwell, James W.; Kollman, Peter A.
  Journal of the American Chemical Society (1995), 117 (19), 5179-97CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
  The authors present the derivation of a new mol. mech. force field for simulating the structures, conformational energies, and interaction energies of proteins, nucleic acids, and many related org. mols. in condensed phases. This effective two-body force field is the successor to the Weiner et al. force field and was developed with some of the same philosophies, such as the use of a simple diagonal potential function and electrostatic potential fit atom centered charges. The need for a 10-12 function for representing hydrogen bonds is no longer necessary due to the improved performance of the new charge model and new van der Waals parameters. These new charges are detd. using a 6-31G* basis set and restrained electrostatic potential (RESP) fitting and have been shown to reproduce interaction energies, free energies of solvation, and conformational energies of simple small mols. to a good degree of accuracy. Furthermore, the new RESP charges exhibit less variability as a function of the mol. conformation used in the charge detn. The new van der Waals parameters have been derived from liq. simulations and include hydrogen parameters which take into account the effects of any geminal electroneg. atoms. The bonded parameters developed by Weiner et al. were modified as necessary to reproduce exptl. vibrational frequencies and structures. Most of the simple dihedral parameters have been retained from Weiner et al., but a complex set of .vphi. and ψ parameters which do a good job of reproducing the energies of the low-energy conformations of glycyl and alanyl dipeptides was developed for the peptide backbone.
44. 44
  Lilien, R. H.; Stevens, B. W.; Anderson, A. C.; Donald, B. R. A novel ensemble-based scoring and search algorithm for protein redesign and its application to modify the substrate specificity of the gramicidin synthetase a phenylalanine adenylation enzyme J. Comput. Biol. 2005, 12, 740– 761
  44
  A Novel Ensemble-Based Scoring and Search Algorithm for Protein Redesign and Its Application to Modify the Substrate Specificity of the Gramicidin Synthetase A Phenylalanine Adenylation Enzyme
  Lilien, Ryan H.; Stevens, Brian W.; Anderson, Amy C.; Donald, Bruce R.
  Journal of Computational Biology (2005), 12 (6), 740-761CODEN: JCOBEM; ISSN:1066-5277. (Mary Ann Liebert, Inc.)
  Realization of novel mol. function requires the ability to alter mol. complex formation. Enzymic function can be altered by changing enzyme-substrate interactions via modification of an enzyme's active site. A redesigned enzyme may either perform a novel reaction on its native substrates or its native reaction on novel substrates. A no. of computational approaches have been developed to address the combinatorial nature of the protein redesign problem. These approaches typically search for the global min. energy conformation among an exponential no. of protein conformations. We present a novel algorithm for protein redesign, which combines a statistical mechanics-derived ensemble-based approach to computing the binding const. with the speed and completeness of a branch-and-bound pruning algorithm. In addn., we developed an efficient deterministic approxn. algorithm, capable of approximating our scoring function to arbitrary precision. In practice, the approxn. algorithm decreases the execution time of the mutation search by a factor of ten. To test our method, we examd. the Phe-specific adenylation domain of the nonribosomal peptide synthetase gramicidin synthetase A (GrsA-PheA). Ensemble scoring, using a rotameric approxn. to the partition functions of the bound and unbound states for GrsA-PheA, is first used to predict binding of the wild-type protein and a previously described mutant (selective for leucine), and second, to switch the enzyme specificity toward leucine, using two novel active site sequences computationally predicted by searching through the space of possible active site mutations. The top scoring in silico mutants were created in the wet-lab. and dissocn./binding consts. were detd. by fluorescence quenching. These tested mutations exhibit the desired change in specificity from Phe to Leu. Our ensemble-based algorithm, which flexibly models both protein and ligand using rotamer-based partition functions, has application in enzyme redesign, the prediction of protein-ligand binding, and computer-aided drug design.
45. 45
  Lee, M. R.; Baker, D.; Kollman, P. A. 2.1 and 1.8 Å average Cα rmsd structure predictions on two small proteins, HP-36 and S15 J. Am. Chem. Soc. 2001, 123, 1040– 1046
  There is no corresponding record for this reference.
46. 46
  Rohl, C. A.; Baker, D. De novo determination of protein backbone structure from residual dipolar couplings using Rosetta J. Am. Chem. Soc. 2002, 124, 2723– 2729
  There is no corresponding record for this reference.
47. 47
  Rohl, C. A.; Strauss, C. E. M.; Misura, K. M. S.; Baker, D. Protein structure prediction using Rosetta. In Methods in Enzymology; Elsevier: San Diego, CA, 2004; Vol. 383, pp 66– 93.
  There is no corresponding record for this reference.
48. 48
  DiMaggio, P. A.; McAllister, S. R.; Floudas, C. A.; Feng, X.-J.; Rabinowitz, J. D.; Rabitz, H. A. Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies BMC Bioinf. 2008, 9, 458
  48
  Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies
  DiMaggio Peter A Jr; McAllister Scott R; Floudas Christodoulos A; Feng Xiao-Jiang; Rabinowitz Joshua D; Rabitz Herschel A
  BMC bioinformatics (2008), 9 (), 458 ISSN:.
  BACKGROUND: The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem in the analysis of gene expression data since genes may only jointly respond over a subset of conditions. Biclustering algorithms also have important applications in sample classification where, for instance, tissue samples can be classified as cancerous or normal. Many of the methods for biclustering, and clustering algorithms in general, utilize simplified models or heuristic strategies for identifying the "best" grouping of elements according to some metric and cluster definition and thus result in suboptimal clusters. RESULTS: In this article, we present a rigorous approach to biclustering, OREO, which is based on the Optimal RE-Ordering of the rows and columns of a data matrix so as to globally minimize the dissimilarity metric. The physical permutations of the rows and columns of the data matrix can be modeled as either a network flow problem or a traveling salesman problem. Cluster boundaries in one dimension are used to partition and re-order the other dimensions of the corresponding submatrices to generate biclusters. The performance of OREO is tested on (a) metabolite concentration data, (b) an image reconstruction matrix, (c) synthetic data with implanted biclusters, and gene expression data for (d) colon cancer data, (e) breast cancer data, as well as (f) yeast segregant data to validate the ability of the proposed method and compare it to existing biclustering and clustering methods. CONCLUSION: We demonstrate that this rigorous global optimization method for biclustering produces clusters with more insightful groupings of similar entities, such as genes or metabolites sharing common functions, than other clustering and biclustering algorithms and can reconstruct underlying fundamental patterns in the data for several distinct sets of data matrices arising in important biological applications.
49. 49
  DiMaggio, P. A., Jr; McAllister, S. R.; Floudas, C. A.; Feng, X.-J.; Rabinowitz, J. D.; Rabitz, H. A. A network flow model for biclustering via optimal re-ordering of data matrices J. Global Optim. 2010, 47, 343– 354
  There is no corresponding record for this reference.
50. 50
  Gray, J. J.; Moughon, S.; Wang, C.; Schueler-Furman, O.; Kuhlman, B.; Rohl, C. A.; Baker, D. Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations J. Mol. Biol. 2003, 331, 281– 299
  50
  Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations
  Gray, Jeffrey J.; Moughon, Stewart; Wang, Chu; Schueler-Furman, Ora; Kuhlman, Brian; Rohl, Carol A.; Baker, David
  Journal of Molecular Biology (2003), 331 (1), 281-299CODEN: JMOBAK; ISSN:0022-2836. (Elsevier Science Ltd.)
  Protein-protein docking algorithms provide a means to elucidate structural details for presently unknown complexes. Here, we present and evaluate a new method to predict protein-protein complexes from the coordinates of the unbound monomer components. The method employs a low-resoln., rigid-body, Monte Carlo search followed by simultaneous optimization of backbone displacement and side-chain conformations using Monte Carlo minimization. Up to 105 independent simulations are carried out, and the resulting "decoys" are ranked using an energy function dominated by van der Waals interactions, an implicit solvation model, and an orientation-dependent hydrogen bonding potential. Top-ranking decoys are clustered to select the final predictions. Small-perturbation studies reveal the formation of binding funnels in 42 of 54 cases using coordinates derived from the bound complexes and in 32 of 54 cases using independently detd. coordinates of one or both monomers. Exptl. binding affinities correlate with the calcd. score function and explain the predictive success or failure of many targets. Global searches using one or both unbound components predict at least 25% of the native residue-residue contacts in 28 of the 32 cases where binding funnels exist. The results suggest that the method may soon be useful for generating models of biol. important complexes from the structures of the isolated components, but they also highlight the challenges that must be met to achieve consistent and accurate prediction of protein-protein interactions.
51. 51
  Kuhlman, B.; Baker, D. Native protein sequences are close to optimal for their structures Proc. Natl. Acad. Sci. U.S.A. 2000, 97, 10383– 10388
  51
  Native protein sequences are close to optimal for their structures
  Kuhlman, Brian; Baker, David
  Proceedings of the National Academy of Sciences of the United States of America (2000), 97 (19), 10383-10388CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
  How large is the vol. of sequence space that is compatible with a given protein structure. Starting from random sequences, low free energy sequences were generated for 108 protein backbone structures by using a Monte Carlo optimization procedure and a free energy function based primarily on Lennard-Jones packing interactions and the Lazaridis-Karplus implicit solvation model. Remarkably, in the designed sequences 51% of the core residues and 27% of all residues were identical to the amino acids in the corresponding positions in the native sequences. The lowest free energy sequences obtained for ensembles of native-like backbone structures were also similar to the native sequence. Furthermore, both the individual residue frequencies and the covariances between pairs of positions obsd. in the very large SH3 domain family were recapitulated in core sequences designed for SH3 domain structures. Taken together, these results suggest that the vol. of sequence space optimal for a protein structure is surprisingly restricted to a region around the native sequence.
52. 52
  Drew, K.; Renfrew, P. D.; Craven, T. W.; Butterfoss, G. L.; Chou, F.-C.; Lyskov, S.; Bullock, B. N.; Watkins, A.; Labonte, J. W.; Pacella, M.; Kilambi, K. P.; Leaver-Fay, A.; Kuhlman, B.; Gray, J. J.; Bradley, P.; Kirshenbaum, K.; Arora, P. S.; Das, R.; Bonneau, R. Adding diverse noncanonical backbones to Rosetta: enabling peptidomimetic design PLoS One 2013, 8, e67051
  There is no corresponding record for this reference.
53. 53
  Renfrew, P. D.; Choi, E. J.; Bonneau, R.; Kuhlman, B. Incorporation of noncanonical amino acids into Rosetta and use in computational protein-peptide interface design PLoS One 2012, 7, e32637
  53
  Incorporation of noncanonical amino acids into Rosetta and use in computational protein-peptide interface design
  Renfrew, P. Douglas; Choi, Eun Jung; Bonneau, Richard; Kuhlman, Brian
  PLoS One (2012), 7 (3), e32637CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)
  Noncanonical amino acids (NCAAs) can be used in a variety of protein design contexts. For example, they can be used in place of the canonical amino acids (CAAs) to improve the biophys. properties of peptides that target protein interfaces. We describe the incorporation of 114 NCAAs into the protein-modeling suite Rosetta. We describe our methods for building backbone dependent rotamer libraries and the parameterization and construction of a scoring function that can be used to score NCAA contg. peptides and proteins. We validate these addns. to Rosetta and our NCAA-rotamer libraries by showing that we can improve the binding of a calpastatin derived peptides to calpain-1 by substituting NCAAs for native amino acids using Rosetta. Rosetta (executables and source), auxiliary scripts and code, and documentation can be found at online.
54. 54
  Mills, J. H.; Khare, S. D.; Bolduc, J. M.; Forouhar, F.; Mulligan, V. K.; Lew, S.; Seetharaman, J.; Tong, L.; Stoddard, B. L.; Baker, D. Computational design of an unnatural amino acid dependent metalloprotein with atomic level accuracy J. Am. Chem. Soc. 2013, 135, 13393– 13399
  54
  Computational Design of an Unnatural Amino Acid Dependent Metalloprotein with Atomic Level Accuracy
  Mills, Jeremy H.; Khare, Sagar D.; Bolduc, Jill M.; Forouhar, Farhad; Mulligan, Vikram Khipple; Lew, Scott; Seetharaman, Jayaraman; Tong, Liang; Stoddard, Barry L.; Baker, David
  Journal of the American Chemical Society (2013), 135 (36), 13393-13399CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
  Genetically encoded unnatural amino acids could facilitate the design of proteins and enzymes of novel function, but correctly specifying sites of incorporation and the identities and orientations of surrounding residues represents a formidable challenge. Computational design methods have been used to identify optimal locations for functional sites in proteins and design the surrounding residues but have not incorporated unnatural amino acids in this process. The authors extended the Rosetta design methodol. to design metalloproteins in which the amino acid (2,2'-bipyridin-5-yl)-alanine (Bpy-Ala) is a primary ligand of a bound metal ion. Following initial results that indicated the importance of buttressing the Bpy-Ala amino acid, the authors designed a buried metal binding site with octahedral coordination geometry consisting of Bpy-Ala, two protein-based metal ligands, and two metal-bound water mols. Exptl. characterization revealed a Bpy-Ala-mediated metalloprotein with the ability to bind divalent cations including Co2+, Zn2+, Fe2+, and Ni2+, with a Kd for Zn2+ of ∼40 pM. X-ray crystal structures of the designed protein bound to Co2+ and Ni2+ have RMSDs to the design model of 0.9 and 1.0 Å resp. over all atoms in the binding site.
55. 55
  Yu, H.; Daura, X.; van Gunsteren, W. F. Molecular dynamics simulations of peptides containing an unnatural amino acid: dimerization, folding, and protein binding Proteins 2004, 54, 116– 127
  There is no corresponding record for this reference.
56. 56
  Daura, X.; van Gunsteren, W. F.; Mark, A. E. Folding-unfolding thermodynamics of a beta-heptapeptide from equilibrium simulations Proteins 1999, 34, 269– 280
  There is no corresponding record for this reference.
57. 57
  Daura, X.; Gademann, K.; Schäfer, H.; Jaun, B.; Seebach, D.; van Gunsteren, W. F. The β-peptide hairpin in solution: conformational study of a β-hexapeptide in methanol by NMR spectroscopy and MD simulation J. Am. Chem. Soc. 2001, 123, 2393– 2404
  57
  The β-Peptide Hairpin in Solution: Conformational Study of a β-Hexapeptide in Methanol by NMR Spectroscopy and MD Simulation
  Daura, Xavier; Gademann, Karl; Schaefer, Heiko; Jaun, Bernhard; Seebach, Dieter; van Gunsteren, Wilfred F.
  Journal of the American Chemical Society (2001), 123 (10), 2393-2404CODEN: JACSAT; ISSN:0002-7863. (American Chemical Society)
  The structural and thermodn. properties of a 6-residue β-peptide I that was designed to form a hairpin conformation have been studied by NMR spectroscopy and mol. dynamics simulation in methanol soln. The predicted hairpin would be characterized by a 10-membered hydrogen-bonded turn involving residues 3 and 4, and two extended antiparallel strands. The interproton distances and backbone torsional dihedral angles derived from the NMR expts. at room temp. are in general terms compatible with the hairpin conformation. Two trajectories of system configurations from 100-ns mol.-dynamics simulations of the peptide in soln. at 298 and 340 K have been analyzed. In both simulations, reversible folding to the hairpin conformation is obsd. Interestingly, there is a significant conformational overlap between the unfolded state of the peptide at each of the temps. As already obsd. in previous studies of peptide folding, the unfolded state is composed of a (relatively) small no. of predominant conformers and in this case lacks any type of secondary-structure element. The trajectories provide an excellent ground for the interpretation of the NMR-derived data in terms of ensemble avs. and distributions as opposed to single-conformation interpretations. From this perspective, a relative population of the hairpin conformation of 20% to 30% would suffice to explain the NMR-derived data. Surprisingly, however, the ensemble of structures from the simulation at 340 K reproduces more accurately the NMR-derived data than the ensemble from the simulation at 298 K, and this point needs further investigation.
58. 58
  Schäfer, H.; Daura, X.; Mark, A. E.; van Gunsteren, W. F. Entropy calculations on a reversibly folding peptide: changes in solute free energy cannot explain folding behavior Proteins 2001, 43, 45– 56
  There is no corresponding record for this reference.
59. 59
  Rathore, N.; Gellman, S. H.; de Pablo, J. J. Thermodynamic stability of β-peptide helices and the role of cyclic residues Biophys. J. 2006, 91, 3425– 3435
  There is no corresponding record for this reference.
60. 60
  McGovern, M.; Abbott, N.; de Pablo, J. J. Dimerization of helical β-peptides in solution Biophys. J. 2012, 102, 1435– 1442
  There is no corresponding record for this reference.
61. 61
  Khoury, G. A.; Thompson, J. P.; Smadbeck, J.; Kieslich, C. A.; Floudas, C. A. Forcefield_PTM: ab initio charge and AMBER forcefield parameters for frequently occurring post-translational modifications J. Chem. Theory Comput. 2013, 9, 5653– 5674
  61
  Forcefield_PTM: Ab Initio Charge and AMBER Forcefield Parameters for Frequently Occurring Post-Translational Modifications
  Khoury, George A.; Thompson, Jeff P.; Smadbeck, James; Kieslich, Chris A.; Floudas, Christodoulos A.
  Journal of Chemical Theory and Computation (2013), 9 (12), 5653-5674CODEN: JCTCCE; ISSN:1549-9618. (American Chemical Society)
  The authors introduce Forcefield_PTM, a set of AMBER forcefield parameters consistent with ff03 for 32 common post-translational modifications. Partial charges were calcd. through ab initio calcns. and a two-stage RESP-fitting procedure in an ether-like implicit solvent environment. The charges are generally consistent with others previously reported for phosphorylated amino acids, and trimethyllysine, using different parametrization methods. Pairs of modified structures and their corresponding unmodified structures were curated from the PDB for both single and multiple modifications. Background structural similarity was assessed in the context of secondary and tertiary structures from the global data set. Next, the charges derived for Forcefield_PTM were tested on a macroscopic scale using unrestrained all-atom Langevin mol. dynamics simulations in AMBER for 34 (17 pairs of modified/unmodified) systems in implicit solvent. Assessment was performed in the context of secondary structure preservation, stability in energies, and correlations between the modified and unmodified structure trajectories on the aggregate. As an illustration of their utility, the parameters were used to compare the structural stability of the phosphorylated and dephosphorylated forms of OdhI. Microscopic comparisons between quantum and AMBER single point energies along key χ torsions on several PTMs were performed, and corrections to improve their agreement in terms of mean-squared errors and squared correlation coeffs. were parametrized. This forcefield for post-translational modifications in condensed-phase simulations can be applied to a no. of biol. relevant and timely applications including protein structure prediction, protein and peptide design, and docking and to study the effect of PTMs on folding and dynamics. The authors make the derived parameters and an assocd. interactive webtool capable of performing post-translational modifications on proteins using Forcefield_PTM available at http://selene.princeton.edu/FFPTM.
62. 62
  Khoury, G. A.; Smadbeck, J.; Tamamis, P.; Vandris, A. C.; Kieslich, C. A.; Floudas, C. A. Forcefield_NCAA: ab initio charge parameters to aid in the discovery and design of therapeutic proteins and peptides with unnatural amino acids and their application to complement inhibitors of the compstatin family. ACS Synth. Biol. [Online early access]. DOI: DOI: 10.1021/sb400168u. Published Online: January 6, 2014.
  There is no corresponding record for this reference.
63. 63
  Mills, J. E.; Dean, P. M. Three-dimensional hydrogen-bond geometry and probability information from a crystal survey J. Comput.-Aided Mol. Des. 1996, 10, 607– 622
  63
  Three-dimensional hydrogen-bond geometry and probability information from a crystal survey
  Mills, J.E.J.; Dean, P.M.
  Journal of Computer-Aided Molecular Design (1996), 10 (6), 607-622CODEN: JCADEQ; ISSN:0920-654X. (ESCOM)
  An extensive crystal survey of the Cambridge Structural Database has been carried out to provide hydrogen-bond data for use in drug-design strategies. Previous crystal surveys have generated 1D frequency distributions of hydrogen-bond distances and angles, which are not sufficient to model the hydrogen bond as a ligand-receptor interaction. For each hydrogen-bonding group of interest to the drug designer, geometric hydrogen-bond criteria have been derived. The 3D distribution of complementary atoms about each hydrogen-bonding group has been ascertained by dividing the space about each group into bins of equal vol. and continuing the no. of obsd. hydrogen-bonding contacts in each bin. Finally, the propensity of each group to form a hydrogen bond has been calcd. Together, these data can be used to predict the potential site points with which a ligand could interact and therefore could be used in mol.-similarity studies, pharmacophore query searching of databases, or de novo design algorithms.
64. 64
  Pettersen, E. F.; Goddard, T. D.; Huang, C. C.; Couch, G. S.; Greenblatt, D. M.; Meng, E. C.; Ferrin, T. E. UCSF Chimera: a visualization system for exploratory research and analysis J. Comput. Chem. 2004, 25, 1605– 1612
  64
  UCSF Chimera-A visualization system for exploratory research and analysis
  Pettersen, Eric F.; Goddard, Thomas D.; Huang, Conrad C.; Couch, Gregory S.; Greenblatt, Daniel M.; Meng, Elaine C.; Ferrin, Thomas E.
  Journal of Computational Chemistry (2004), 25 (13), 1605-1612CODEN: JCCHDD; ISSN:0192-8651. (John Wiley & Sons, Inc.)
  The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale mol. assemblies such as viral coats, and Collab., which allows researchers to share a Chimera session interactively despite being at sep. locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and assocd. structures; ViewDock, for screening docked ligand orientations; Movie, for replaying mol. dynamics trajectories; and Vol. Viewer, for display and anal. of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/.
65. 65
  Hubbart, S. J.; Thornton, J. M.NACCESS (computer program); Department of Biochemistry and Molecular Biology, University College London: London, 1993.
  There is no corresponding record for this reference.
66. 66
  Bellows, M. L.; Taylor, M. S.; Cole, P. A.; Shen, L.; Siliciano, R. F. Discovery of entry inhibitors for HIV-1 via a new de novo protein design framework Biophys. J. 2010, 99, 3445– 3453
  There is no corresponding record for this reference.
67. 67
  Bellows, M. L.; Floudas, C. A. Computational methods for de novo protein design and its applications to the human immunodeficiency virus 1, purine nucleoside phosphorylase, ubiquitin specific protease 7, and histone demethylases Curr. Drug Targets 2010, 11, 264– 278
  67
  Computational methods for de novo protein design and its applications to the human immunodeficiency virus 1, purine nucleoside phosphorylase, ubiquitin specific protease 7, and histone demethylases
  Bellows, M. L.; Floudas, C. A.
  Current Drug Targets (2010), 11 (3), 264-278CODEN: CDTUAU; ISSN:1389-4501. (Bentham Science Publishers Ltd.)
  A review. This paper provides an overview of computational de novo protein design methods, highlighting recent advances and successes. Four protein systems are described that are important targets for drug design: human immunodeficiency virus 1, purine nucleoside phosphorylase, ubiquitin specific protease 7, and histone demethylases. Target areas for drug design for each protein are described, along with known inhibitors, focusing on peptidic inhibitors, but also describing some small-mol. inhibitors. Computational design methods that have been employed in elucidating these inhibitors for each protein are outlined, along with steps that can be taken in order to apply computational protein design to a system that has mainly used exptl. methods to date.
68. 68
  Bellows-Peterson, M. L.; Fung, H. K.; Floudas, C. A.; Kieslich, C. A.; Zhang, L.; Morikis, D.; Wareham, K. J.; Monk, P. N.; Hawksworth, O. A.; Woodruff, T. M. De novo peptide design with C3a receptor agonist and antagonist activities: theoretical predictions and experimental validation J. Med. Chem. 2012, 55, 4159– 4168
  There is no corresponding record for this reference.
69. 69
  Bellows, M. L.; Fung, H. K.; Floudas, C. A. Recent advances in de novo protein design. In Molecular Systems Engineering; Adjiman, C. S.; Galindo, A., Eds.; Process Systems Engineering, Vol. 6; Wiley-VCH: Weinheim, Germany, 2010; pp 207– 232.
  There is no corresponding record for this reference.
70. 70
  Case, D. A.; Darden, T. A.; Cheatham, T. E., III; Simmerling, C. L.; Wang, J.; Duke, R. E.; Luo, R.; Walker, R. C.; Zhang, W.; Merz, K. M.; Roberts, B.; Wang, B.; Hayik, S.; Roitberg, A.; Seabra, G.; Kolossváry, I.; Wong, K. F.; Paesani, F.; Vanicek, J.; Liu, J.; Wu, X.; Brozell, S. R.; Steinbrecher, T.; Gohlke, H.; Cai, Q.; Ye, X.; Wang, J.; Hsieh, M.-J.; Cui, G.; Roe, D. R.; Mathews, D. H.; Seetin, M. G.; Sagui, C.; Babin, V.; Luchko, T.; Gusarov, S.; Kovalenko, A.; Kollman, P. A.AMBER 11; University of California: San Francisco, CA, 2010.
  There is no corresponding record for this reference.
71. 71
  Onufriev, A.; Bashford, D.; Case, D. A. Modification of the generalized Born model suitable for macromolecules J. Phys. Chem. B 2000, 104, 3712– 3720
  71
  Modification of the Generalized Born Model Suitable for Macromolecules
  Onufriev, Alexey; Bashford, Donald; Case, David A.
  Journal of Physical Chemistry B (2000), 104 (15), 3712-3720CODEN: JPCBFK; ISSN:1089-5647. (American Chemical Society)
  The analytic generalized Born approxn. is an efficient electrostatic model that describes mols. in soln. Here it is modified to permit a more accurate description of large macromols., while its established performance on small compds. is nearly unaffected. The modified model is also adapted to describe mols. with an interior dielec. const. not equal to unity. The model was tested by computations of pK shifts for a no. of titratable residues in lysozyme, myoglobin, and bacteriorhodopsin. In general, except for some deeply buried residues of bacteriorhodopsin, the results show reasonable agreement with both exptl. data and calcns. based on numerical soln. of the Poisson-Boltzmann equation. A very close agreement between the two models is obtained in prediction of the pK shifts assocd. with conformational change. The calcns. based on this version of the generalized Born approxn. are much faster than finite difference solns. of the Poisson-Boltzmann equation, which makes the present method useful for a variety of other applications where computational time is a crit. factor. The model may also be integrated into mol. dynamics programs to replace explicit solvent simulations which are particularly time-consuming for large mols.
72. 72
  Onufriev, A.; Bashford, D.; Case, D. A. Exploring protein native states and large-scale conformational changes with a modified generalized Born model Proteins 2004, 55, 383– 394
  72
  Exploring protein native states and large-scale conformational changes with a modified Generalized Born model
  Onufriev, Alexey; Bashford, Donald; Case, David A.
  Proteins: Structure, Function, and Bioinformatics (2004), 55 (2), 383-394CODEN: PSFBAF ISSN:. (Wiley-Liss, Inc.)
  Implicit solvation models provide, for many applications, a reasonably accurate and computationally effective way to describe the electrostatics of aq. solvation. Here, a popular anal. Generalized Born (GB) solvation model is modified to improve its accuracy in calcg. the solvent polarization part of free energy changes in large-scale conformational transitions, such as protein folding. In contrast to an earlier GB model (implemented in the AMBER-6 program), the improved version does not overstabilize the native structures relative to the finite-difference Poisson-Boltzmann continuum treatment. In addn. to improving the energy balance between folded and unfolded conformers, the algorithm (available in the AMBER-7 and NAB mol. modeling packages) is shown to perform well in more than 50 ns of native-state mol. dynamics (MD) simulations of thioredoxin, protein-A, and ubiquitin, as well as in a simulation of Barnase/Barstar complex formation. For thioredoxin, various combinations of input parameters have been explored, such as the underlying gas-phase force fields and the at. radii. The best performance is achieved with a previously proposed modification to the torsional potential in the Amber ff99 force field, which yields stable native trajectories for all of the tested proteins, with back-bone root-mean-square deviations from the native structures being ∼ 1.5 Å after 6 ns of simulation time. The structure of Barnase/Barstar complex is regenerated, starting from an unbound state, to within 1.9 Å relative to the crystal structure of the complex.
73. 73
  Johnson, L. V.; Forest, D. L.; Banna, C. D.; Radeke, C. M.; Maloney, M. A.; Hu, J.; Spencer, C. N.; Walker, A. M.; Tsie, M. S.; Bok, D.; Radeke, M. J.; Anderson, D. H. Cell culture model that mimics drusen formation and triggers complement activation associated with age-related macular degeneration Proc. Natl. Acad. Sci. U.S.A. 2011, 1, 18277– 18282
  There is no corresponding record for this reference.
74. 74
  Henchoz, Y.; Bard, B.; Guillarme, D.; Carrupt, P.-A.; Veuthey, J.-L.; Martel, S. Analytical tools for the physicochemical profiling of drug candidates to predict absorption/distribution Anal. Bioanal. Chem. 2009, 394, 707– 729
  74
  Analytical tools for the physicochemical profiling of drug candidates to predict absorption/distribution
  Henchoz, Yveline; Bard, Bruno; Guillarme, Davy; Carrupt, Pierre-Alain; Veuthey, Jean-Luc; Martel, Sophie
  Analytical and Bioanalytical Chemistry (2009), 394 (3), 707-729CODEN: ABCNBP; ISSN:1618-2642. (Springer)
  A review. The measurement of physicochem. properties at an early phase of drug discovery and development is crucial to reduce attrition rates due to poor biopharmaceutical properties. Among these properties, ionization, lipophilicity, soly. and permeability are mandatory to predict the pharmacokinetic behavior of NCEs (new chem. entities). Due to the high no. of NCEs, the anal. tools used to measure these properties are automated and progressively adapted to high-throughput technologies. The present review is dedicated to exptl. methods applied in the early drug discovery process for the detn. of soly., ionization consts., lipophilicity and permeability of small mols. The principles and exptl. conditions of the different methods are described, and important enhancements in terms of throughput are highlighted.
- PDB: 2QKI
Supporting Information
Supporting Information
Tables and figures of peptide design rankings, compstatin peptide inhibitory activity (from ELISAs, hemolytic assays, and cell based RPE assays), and solubility/lipophilicity data. This material is available free of charge via the Internet at http://pubs.acs.org.
- jm501345y_si_001.pdf (235.01 kb)
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New Compstatin Peptides Containing N-Terminal Extensions and Non-Natural Amino Acids Exhibit Potent Complement Inhibition and Improved Solubility CharacteristicsClick to copy article linkArticle link copied!

Journal of Medicinal Chemistry

Abstract

Introduction

Figure 1

Results

Complement Inhibition in ELISA and Hemolytic Assays

Figure 2

Figure 3

Complement Inhibition in Retinal Pigmented Epithelial Cell Model

Figure 4

Figure 5

Solubility of Compstatin Peptides

Figure 6

Relative Lipophilicity of Compstatin Peptides

Figure 7

Discussion

Experimental Section

De Novo Peptide Design with Natural Amino Acids

Sequence Selection

Fold Specificity

Approximate Binding Affinity

De Novo Peptide Design with Non-Natural Amino Acids

Constraints That Must be Met for Inclusion in Set Mp

Binary Decision Variables

Peptide Synthesis

Solubility Measurements

C3b and C5b-9 ELISA

Hemolytic Assays

RPE Cell Culture

Immunohistochemistry

Confocal Imaging and Analysis

RP-HPLC Study

Supporting Information

Terms & Conditions

Author Information

Acknowledgment

Abbreviations Used

References

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Journal of Medicinal Chemistry

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Abstract

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Figure 3

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Figure 5

Figure 6

Figure 7

References

Supporting Information

Supporting Information

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New Compstatin Peptides Containing N-Terminal Extensions and Non-Natural Amino Acids Exhibit Potent Complement Inhibition and Improved Solubility Characteristics
Click to copy article linkArticle link copied!

Constraints That Must be Met for Inclusion in Set M_p