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Identification of Novel Liver X Receptor Activators by Structure-Based Modeling

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† Institute of General, Inorganic and Theoretical Chemistry/Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80/82, A-6020 Innsbruck, Austria

‡ Computer-Aided Molecular Design (CAMD) Group and CMBI, Institute of Pharmacy/Pharmaceutical Chemistry, University of Innsbruck, Innrain 80/82, A-6020 Innsbruck, Austria

§ Institute of Pharmacy/Pharmaceutical Chemistry, Freie Universitaet Berlin, Koenigin Luise Strasse 2 + 4, D-14195 Berlin, Germany

∥ Department of Vascular Biology and Thrombosis Research, Medical University of Vienna, Schwarzspanierstrasse 17, A-1090 Wien, Austria

*E-mail: [email protected]

Cite this: J. Chem. Inf. Model. 2012, 52, 5, 1391–1400

Publication Date (Web):April 10, 2012

https://doi.org/10.1021/ci300096c

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Abstract

Liver X receptors (LXRs) are members of the nuclear receptor family. Activators of LXRs are of high pharmacological interest as LXRs regulate cholesterol, fatty acid, and carbohydrate metabolism as well as inflammatory processes. On the basis of different X-ray crystal structures, we established a virtual screening workflow for the identification of novel LXR modulators. A two-step screening concept to identify active compounds included 3D-pharmacophore filters and rescoring by shape alignment. Eighteen virtual hits were tested in vitro applying a reporter gene assay, where concentration-dependent activity was proven for four novel lead structures. The most active compound 10, a 1,4-naphthochinone, has an estimated EC₅₀ of around 5 μM.

Introduction

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Liver X receptors (LXRs) are members of the nuclear receptor family. The two subtypes α and β are classified in a homology-based nomenclature system as NR1H3 and NR1H2, respectively. (1) As lipid-activated nuclear receptors, they are composed of a highly conserved DNA binding domain (DBD) and a ligand binding domain (LBD), which can be targeted by endogenous ligands (oxidized cholesterol derivates), (2) as well as by synthetic ligands. (3) The regulatory impact of nuclear receptors on gene expression is linked with a conformational rearrangement of the LBD upon ligand binding, the dissociation of assembled corepressors or the recruitment of coactivators, and induced transcription effected by the DBD of the nuclear receptors. Enhanced transrepression of associated genes via LXR activation needs further studies, though already some insights in the complex inflammation related signaling pathways could be gained, as reviewed by Bensinger et al. (4, 5)

The physiological impact of LXR is associated with the communicative interface of lipid metabolism and inflammation. (6, 3) Therefore, the LXRs were identified as a promising drug target for indications such as hypercholesterolemia, atherosclerosis, and cardiovascular diseases. (7, 4) Identification of first potent LXR agonists (8) and convenient results in vivo, such as promising experiments with atherosclerotic mice (9) motivated medicinal chemistry campaigns. Accelerated by insights into the molecular structure of the LXR LBD, various LXR-modulating scaffolds were identified and reviewed in refs 10 and 11. A striking setback on the road to the clinical application of LXR agonists is the increase of triglyceride levels in animal studies. (5) Strategies to overcome this side effect related with LXRα activation is the development of LXRβ-selective activators (12-14) or tissue-specific LXR modulators. (15) Detailed investigations revealed that the complex regulation processes in lipid metabolism might be considered as critical with regard to further potential side effects. (16) Nevertheless, potential uses as drug target remain attractive and the development of LXR modulators also including antagonists is an attractive research field. (17) Recently, LXR signaling was linked with acquired immune response, (18) proliferation control, (5) and antitumor response. (19) Furthermore, Alzheimer’s disease (20, 21) and diabetes (22) were added to the potential application fields of LXR modulators.

For the nuclear receptors LXRα and β 10 Brookhaven Protein Data Bank (PDB) entries were deposited from 2003 up to 2009 (Table 1). (23, 24) The secondary structure of nuclear receptor ligand binding domains, dominated by 12 α-helices forming a mainly hydrophobic binding pocket, is highly conserved for the LXR structure of both subtypes. The PDB entry 1pq9 was excluded from this investigation as the ligand was destroyed during X-ray treatment of the crystal. (25) Full chains for the LBD are found in 1pq6, 1pqc, and 3fc6, (25, 26) while the other crystal structures miss the 3D coordinates for several residues related to the flexibility of the protein. The PDB entries differ in resolution, cocrystallized proteins (monomers, homodimers, and physiological heterodimers with retinoid X receptor (RXR)), and the complexed ligands (Figure 1). Compound 1, epoxycholesterol, is an endogenous LXR activator with weaker affinity than some published synthetic nonsteroid ligands. The hexaflouropropanol moiety in the sulfonamide T-0901317, compound 2, (3) was optimized to compound 3 during structure guided design of the amide series by GSK. (27) Pharmacokinetic improvement efforts on compound 5, GW3965, (8) led to the indol substituted compound 6. (26) The maleimide structure of compound 4 represents a further scaffold and was identified by HTS. (28)

Figure 1. LXR modulators cocrystallized in PDB crystal structures.

Table 1. Structural Data Available from PDB Deposits 2003–2009

PDB entry	ligand	resolution [Å]	subtype	gene source	crystal composition	refs
1p8d	1	2.80	β	human	homodimer, synthetic coactivator	39
1pq9	2^a	2.10	β	human	homodimer	25
1pq6	5	2.40	β	human	homodimer	25
1pqc	2	2.80	β	human	homodimer	25
1upv	2	2.10	β	human	monomer	63
1upw	2	2.40	β	human	monomer	63
1uhl	2	2.90	α	human	dimer with RXRβ	64
2acl	4	2.80	α	mouse	dimer with RXRα	28
3fal	3	2.36	α	mouse	dimer with RXRα	27
3fc6	6	2.06	α	mouse	dimer with RXRα	26

Ligand artifact from X-ray experiment.

The published structural insights are a suitable basis for structure-based virtual screening (VS) strategies. The application of an approved computational high throughput screening (HTS) can be a faster and less expensive approach than classical experimental HTS in order to identify new scaffolds for LXR modulators. VS approaches have already been successfully applied on LXR. For instance, the identification of 2-aryl-N-acyl indole as LXR agonist, such as compound 6, was guided by docking experiments. (29) The same working group published a successful docking campaign applying the program GLIDE to identify a further LXR modulating scaffold. (30) Two recent studies, (31, 32) published during the preparation of this manuscript, also used 3D-pharmacophores to establish a VS protocol. Zhao et al. developed a ligand-based quantitative model for LXR agonists and validated their findings by docking. (32) The study of Ghemtio et al. has a similar methodological approach as the study we present here. (31) The authors compared a combination of 3D-pharmacophores and volume restrictions as prefilter for exhaustive docking. (33) However, our study goes a step further, as we included experimental testing of predicted virtual hits and thereby provide evidence for the model’s validity.

Results

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Study Design

Crystallographic data from LXR LBD in complex with bioactive ligands, as found in the freely accessible PDB, (23, 24) provided structural insights into the molecular interactions. In the concept of structure-based 3D-pharmacophores, the interacting features and their geometric relations are derived from the X-ray structures and translated into a pharmacophore model, which can be applied for screening of virtual compound databases reviewed in refs 34 and 35. In our study, we first included the 10 X-ray structures published up to 2009 covering LXR α as well as β, as the biological assay we applied is not suitable to distinguish subtype selectivity (Table 1). The pharmacophores, generated with LigandScout 2.3, (36) were manually modified and theoretically validated before seven pharmacophores derived from different PDB entries were selected for the VS. Applying multiple pharmacophores, we could cover different binding modes related with conformational changes in the binding pocket. The second step of VS was a reranking of the screening hit lists with the TanimotoCombo scoring function of ROCS, a method for fast alignment and comparison to the bioactive ligand conformation as query molecule. (37, 38) The two-step in silico strategy was applied for screening of the National Cancer Institute (NCI) Database (250 761 compounds). Eighteen highly ranked compounds were selected from the hit list by aspects of availability, chemical diversity, and drug-like character for an in vitro transactivation assay, which verified LXR activation for four compounds. The work flow and key data are visualized in Figure 2.

Figure 2. Workflow for finding novel LXR modulators.

LXR Ligand Binding Pocket

The binding sites of the LXRs are mainly hydrophobic and composed of two to three cavities and a tunnel directing to the solvent-exposed residues (C2) (Figure 3). In the C1 cavity, interaction with His435 (His421 in LXRα) is crucial and a hydrogen bond to this residue is supposed to stabilize the stacking of His435 to Trp457 (Trp443 in LXRα) in the C-terminal α-helix (known as helix 12), which favors the association of coactivators next to helix 12. (39) The epoxide oxygen of the endogenous ligand 1 forms this interaction as well as the synthetic compounds. (10) Although the hydrogen bond was described as critical, LXR modulators are known which do not establish a hydrogen bond to His435. (40) Small ligands, like compound 2, fill the C1 and C2 region. The benzylsulfonate moiety extends a little into a wide tunnel, which is also present in the binding pocket with bound endogenous ligand. For comparison, larger molecules show another binding mode, where a third subpocket (C3) can open and accommodate branched hydrophobic substituents. This C3-cavity is formed by three phenylalanine residues. It is opened by an altered side chain conformation of Phe340. The typical features of the binding pocket are reflected in the pharmacophore features.

Figure 3. Binding pocket of compound 2 in 1pqc (A) and compound 5 in 1pq6 (B) with pharmacophore features of the models and highlighted cavity C1 (red), binding tunnel C2 (green), and subpocket C3 (blue); for the benefit of clear arrangement Xvols are hidden. His435, Trp443, and Phe340 are shown in ball and stick style. In part B, Phe340 changes its conformation and opens up the hydrophobic cavity C3 in order to accommodate the larger ligand compound 5.

Pharmacophore Models

The nine pharmacophore models generated based on PDB entries were composed of four to seven features describing ligand–receptor interactions and excluded volumes (Xvols) on protein atoms to line the binding pocket. (36) Initial pharmacophore generation was automated using the LigandScout algorithm and was followed by manual modification of the pharmacophore models. The optimization process aimed at improved enrichment factors, which describes the ratio of found active compounds versus hits from a decoy database (calculated according to the Experimental Section). To achieve a higher yield of active hits in the test set, selected features were deleted or modified. Further manipulations affected the spatial restriction for the pharmacophore models: While the standard approach placed single excluded volumes according to a residue-dependent algorithm (applied for the models 1p8d, 1pqc, 1uhl, 1upv, 1upw, 2acl, and 3fal), an alternative approach composed a coat of excluded volumes with a 0.8 Å tolerance on each heavy atom of the protein in the binding site (applied for the models 1pqc and 3fal). Composition of the nine pharmacophores is depicted in Figure 4, and their validation performance is summarized in Table 1. All pharmacophores besides model 3fc6 have hydrogen bond acceptors (HBA) which describe the interaction to His435. Central hydrophobic features (HF) in the binding site represent the hydrophobic character of the binding site. In model 3fal the additional C3 interaction is represented by a HF; in 3fc6, by a hydrophobic aromatic feature (HAF). In the model 1pq6, a more restrictive aromatic ring feature (AR) takes into account the orientation of the aromatic plane as further criterion for feature mapping as the ligand’s phenyl moiety interacts via aromatic π-stacking to Phe340 (Figure 3). Pharmacophore model 2acl stands out with a very unfavorable enrichment factor. This is related to the distinct chemical scaffold of compound 6 and the fact that 1H-pyrrole-2,5-diones and related compounds were underrepresented in the test set.

The pharmacophores on PDB 1p8d and 1upw were excluded from the application phase of the screening system. With this study focusing on the identification of new nonsteroidal scaffolds, we decided to neglect the model 1p8d based on an endogenous ligand, which produced hit lists dominated by steroids during the validation screening. The enrichment factor of 6.2 for the model 1upw is typical for a crude filter, which could be useful for prescreening when followed by further filters for hit list reduction. In this study, the pharmacophore model 1upw is considered to be inappropriate as the pharmacophores are the only cutoff delimiter. Additionally, the 1upw model produced hits with high overlap to the model 1pqc during validation: only three test set hits of 1upw were not matched by the model of 1pqc. Two of those test set compounds were covered by the models 1upv and 2acl. Therefore, exclusion of the model 1upw only had a minor effect on found actives from the test set, but resulted in a major reduction of the number of found decoys. The seven pharmacophore models used for subsequent screening matched 29 out of 41 active compounds in the test set and showed a combined enrichment factor of 5.2 in the validation screening.

Pharmacophore Screening

The parallel pharmacophore filtering of the NCI database resulted in seven virtual hit lists, one for each pharmacophore. The hit lists were composed of the compounds matching the pharmacophore model’s chemical and geometrical restraints. The number of hits found by each model is displayed in Table 2. Mismatch between the NCI hit lists and the corresponding conformational hit lists is due to molecules failing the conformer generation algorithm of Openeye’s Omega software, e.g. metal-containing compounds. The nonredundant, combined hit lists comprised 19 769 compounds corresponding to a filtering rate of 7.6%.

Table 2. Pharmacophore Characteristics

model code	1p8d ^a	1pq6	1pqc	1upv	1upw ^a	1uhl	2acl	3fal	3fc6	all	all w/o 1p8d 1upw
test set (41)	7	23	9	2	16	7	5	6	9	30	29
decoy set WDI (67050)	464	1699	2370	17	4338	1392	4916	1283	94	11318	9352
EF	24.9	22.4	6.3	176.6	6.2	8.4	1.7	7.8	146.6	4.4	5.2

1p8d and 1upw were not used for subsequent virtual screening.

Table 3. Virtual and Biological Screening Results

model	1pq6	1pqc	1upv	1uhl	2acl	3fal	3fc6	combined
no. of hits from NCI (250 761)	4193	8078	56	2984	1875	5275	244
no. of hits shape alignment	4116	7917	53	2906	1832	5183	243	19769
no. of selected compounds	7	7	2	9	5	6	1	18
no. of active compounds	1	2	1	4	2	1	0	4

Shape Alignment

A subsequent ranking of the hit lists produced by pharmacophore screening was performed with shape based alignment applying Openeye’s software ROCS. Bioactive conformations extracted from the crystal structures served as query molecules for alignment. A combination of shape overlap and chemical feature similarity between reference and the molecules from the hit lists (TanimotoCombo score) were applied for ranking. On the basis of this ranking, we selected 18 compounds for validation tests (Supporting Information, Table S1). The selection included highly ranked hits with conclusive alignment poses, low molecular weight (except one <500 g/mol), and chemical diversity. Three compounds contained a central sulfonamide and four compounds showed an aniline substructure, similar to the query compounds and other known LXR modulators. Nevertheless, the tested compounds also included new scaffolds, e.g., two acridine scaffolds and a 2,3-substituted naphthochinone.

LXR Reporter Assay

For 18 compounds the relative induction of the LXR-driven luciferase reporter gene was determined (Supporting Information, Table S2). Four compounds (7, 8, 9, and 10, Figure 5, Table 4) showed a significant transactivation relative to the induction of ABCA1 transcription by the known LXR modulator 2. Four compounds classified as active were reanalyzed at different compound concentrations (Figure 6). Compound 8 (NSC130822; 6-((benzyl((8-hydroxy-6-quinolinyl)methyl)amino)methyl)-8-quinolinol) and compound 10 (NSC618463; 2-(4-methyl-1Δ⁵-pyridin-1-yl)-3-(3-(trifluoromethyl)anilino)naphthoquinone) induced ABCA1 transcription comparable to the known LXR activators 2 and 5, but in higher concentrations. Compound 7 (NSC130101; 2-((diethylamino)methyl)-4-((4-methoxy-9-acridinyl)amino)phenol) and compound 9 (NSC131747; 4-(3-hydroxy-4-methoxybenzyl)-7-methoxy-8-isoquinolinol) even need concentrations of 50 μM to observe transactivation effects. Compound 9 showed the lowest absolute induction of ABCA1, what is in agreement with the results from relative induction experiments, where compound 9 at 25 μM showed 49.2% of induction compared to 1 μM of compound 2 (Supporting Information, Table S2).

Figure 5. Newly identified LXR agonists and their shape alignment with the query compounds. (A) 7 with query compound 2 of 1upv. (B) 8 with query compound 5 of 1pq6. (C) 9 with query compound 3 of 3fal. (D) 10 with query compound 4 of 2acl.

Figure 6. ABCA1 induction by compounds 7, 8, 9, and 10 at different concentrations. The control includes ABCA1 induction of compound 2 at 1 μM (light gray) and compound 5 at 1 μM (anthracite) as well as unstimulated control with DMSO (gray) and without DMSO (black).

Table 4. Newly Identified LXR Agonists

compound	hitlist, rank (shape-based)	rel induction ± SD^a [%] 1 μM 25 μM
7	1pqc, 3471	13.6 ± 1.4*
	1upv, 5	90.9 ± 9.9*
	1uhl, 106
	2acl, 601
8	1pqc, 2837	44.9 ± 8.8
	1pq6, 42	76.7 ± 24.1
	3fal, 96
9	3fal, 10	6.6 ± 2.7
9	3fal, 10	49.2 ± 10.5*
10	2acl, 55	53.4 ± 17.6
10		109.7 ± 5.7*

SD: standard deviation of three experiments.

Discussion

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The four identified LXR modulators were derived from a VS concept combining pharmacophore screening and rescoring with shape-based alignment.

With regard to the methodological aspects, this study joins a list of other screening approaches, which were already successful for other inflammatory targets and led to the identification of novel compounds targeting inflammation. (41-44) As far as we know, this is the first pharmacophore-based virtual screening published for the target LXR including biological confirmation. Nevertheless, the here presented screening concept for LXR is comparable to the structure based filtering strategies by Ghemtio et al. (31) The authors of the latter primarily focused on the comparative performance of the filters and finally proposed a consensus strategy for LXRβ. In contrast, our study is initially designed with a hierarchically condensation of two methods for VS and included LXRα and LXRβ. Additionally, our study integrated a biological testing for verification. Despite of these differences, we agree in many conceptual and methodological aspects. Similar to our approach, Ghemtio et al. applied parallel pharmacophores and shape filtering based on different crystal structures. The parallel conception is a convenient approach to overcome the challenges of a flexible drug target when multiple different crystal structures are available, as it is the case for LXR. (45, 46)

Pharmacophore filtering and shape alignment, two virtual screening tools known for fast performance, are combined here. To show the synergy by the subsequent use of the two methods within this study, independent performance of both pharmacophore screening and shape alignment were analyzed retrospectively (Supporting Information Table S2 and S3). The four active compounds, 7, 8, 9, and 10 are not ranked within the first 25% of the pharmacophore hit lists with the exception of compound 7 matching the model 1uhl with a good fit value. In respect, shape alignment alone without prefiltering by pharmacophores would not result in a top-ranking (top 500) for the active compounds. Top-ranked hits from both methods applied independently might still be active as no testing was performed to evaluate them as truly negative. However, we can state that neither pharmacophore nor shape alignment alone would have resulted in a selection of the four active compounds identified here. We conclude that the hierarchical combination of pharmacophore screening in a first step and shape alignment in a second one was crucial for the identification of the active LXR modulators.

A principle advantage of the parallel screening approach is that the modular conception allows for easily extending and adapting the approach to new insights. During manuscript preparation a further ligand-bound LXRβ structure was released in the PDB representing the binding mode of 4-(3-aryloxyaryl)quinolines. (47) An additional pharmacophore model based on this new X-ray structure showed a hydrogen bond interaction with Leu330 (Supporting Information, Figure S2). This feature was not yet covered within the set of nine pharmacophore models. This hydrogen bond was suggested for LigandScout’s automated pharmacophore generation in 3fc6 modeling but manually deleted in the model 3fc6 during model optimization. The new model 3kfc is characterized by a good hit rate in the test set (23/41) and partially complements the set of seven used pharmacophores by covering six additional test set compounds. Nevertheless, it shows also a high hit rate within the decoys, and because of this low restrictivity, we suggest not to include this new pharmacophore model 3kfc in further applications of the virtual screening approach.

Regarding the biological results, we could identify compounds 8 and 10 with EC₅₀ around 5 μM and the weaker LXR activators 7 and 9. Three of the active compounds show a molecular weight over 400 g/mol. The smallest compound (9, molecular weight 311.3 g/mol) being the weakest LXR activator in this study is a suitable candidate for lead optimization, as the small scaffold allows the addition of substituents targeting further interaction points within the spacious binding pocket. Compounds 7 and 8 showed more extended structures with four or more aromatic rings. Although the bulky acridine in compound 7 might be a steric challenge, 7 is matched by four pharmacophore models and the alignment within the structure 2acl complex predicts a convenient interaction pattern (Figure 7). Compound 8 showed no top-ranking in the alignment. Motivation to test compound 8 was the frequent occurrence of quinolin-8-ol substructures within the hit lists, and therefore, compound 8 with two quinolin-8-ol moieties and fair ranking within three hit lists was selected.

Figure 7. Alignment of compound 7 in the LXR crystal structure (PDB code 2acl). Five hydrophobic interactions and a hydrogen bond with Ser278 (LXRβ numbering) were identified with LigandScout. His435, Trp443, and Ser278 are shown in ball and stick style.

Compound 10 is of special interest, not only because of the highest activity found in this study but also for its interesting scaffold. The 2,3-substituted naphthochinone is different from known LXR modulators, and it is not surprising, that it was only found by the pharmacophore model 2acl, showing a distinct interaction pattern. (28) Alignment with the maleimide 4 showed perfect overlap for the aromatic substitute (Figure 5D), while the permanent charge of the pyridinyl substructure links to the basic function of other LXR activator classes, e.g. the tertiary amines as present in 3, 5, and 6.

Conclusion

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We presented a VS approach for the metabolic and immunological target LXR. Here the subsequent use of pharmacophore screening and shape alignment has been successful. The four novel compounds 7, 8, 9, and 10 are identified as activators of LXR induced ABCA transactivation with low micromolar EC₅₀ values and transactivation induction in levels comparable to known LXR activators. All four hits can serve as inspiration for lead optimization. Thus, the screening approach was evaluated positively and larger scale application is planned.

Experimental Section

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Software Specification

The following software programs were used for this study: Inte:ligand’s LigandScout 3.0 and Openeye’s VIDA for visualization of 3D figures. Inte:ligand’s LigandScout 2.3 for pharmacophore generation, Accelrys’ Catalyst 4.11 for screening and calculation of multiconformer databases, Openeye’s ROCS 2.4.2 for shape based alignment, and OMEGA 2.3.2 for calculation of multiconformer databases.

Compound Data Sets

Three compound databases were screened during this study. While a set of 41 LXR ligands (test set, Supporting Information, Figure S1) and a decoy set of drug-like compounds, the Derwent World Drug Index 2005 (WDI), were screened for pharmacophore validation, the third database was used for productive virtual screening (NCI database).

Forty-one ligands covering 12 scaffolds composed a validation data set, the so-called test set. The ligand structures and activity information were extracted from literature. We draw on a review by Bennett (10) and references therein, collecting LXR modulators published up to March 2007. Endogenous ligands and more recently published synthetic ligands completed our selection for the test set. (3, 8, 12-14, 26, 30, 48-55) Compounds’ 3D structures were prepared with CORINA 3.0 (56) and the multiconformer database was calculated using Accelrys’ Catalyst 4.11 (57) (catConf settings: maximum number of conformers = 250/molecule, generation type = best quality, max. energy 20 kcal/mol above the calculated energy minimum). The WDI is a commercially available database with 67 050 drugs and biologically active compounds. (58) Here, we used this data set for selectivity check of the pharmacophores and considered these compounds as inactive decoys for the screening. The NCI database is the compound collection provided by the Developmental Therapeutic Program of the National Cancer Institute, (59) and a part of the compounds are provided for experimental research. The NCI data set, release 3, 2003 including 260 071 entries was downloaded and calculated as a multiconformational database using Catalyst for pharmacophore screening resulting in a 250 761 compound library (catconf settings: maximum number of conformers =100/molecule, generation type = fast). The hit lists as well as the NCI Database were calculated as multiconformational databases using OMEGA version 2.3.2 with the default setting to provide a format compatible with ROCS.

Pharmacophore Modeling, Screening, and Validation

The pharmacophores were generated applying LigandScout2.3 with default settings for the detection of protein–ligand interactions. (36) These primary pharmacophores were submitted to manual manipulation to exclude interactions with water molecules. The number of features for the primary pharmacophore models was reduced to make them more suitable for scaffold hopping during validation. VS was performed with the search engine of Accelrys’ Catalyst 4.11 using the best flexible search option. (57)

To validate the models we screened the WDI as a collection of decoys and our test set including 41 LXR modulators. Calculating the enrichment factor (EF) helps to quantify the models discriminatory power:

where TP is the number of active LXR modulators matched by the model, n is the sum of LXR modulators and decoys matched by the model, A is the number of active LXR modulators within the test set, and N is the number of all compounds in the validation data sets. (60)

Shape Alignment

The command line application ROCS 2.4.2 performs automated alignment of investigated compounds to a query molecule optimizing the overlap of the shape, which is characterized by a sum of continuous Gaussian functions. (38) ROCS optimizes the shape overlap and produces a scoring function according to the Tanimoto equation,

where I terms are the self-volume overlaps for the query molecule f and a compared molecule g and the overlap O_f,g, was maximized during alignment.

A further ROCS score is the ColorTanimoto, which calculates the overlap of the six chemical features (hydrogen-bond donors, hydrogen-bond acceptors, hydrophobes, anions, cations, and rings), defined with the ImplicitMillsDean force field. (61) The TanimotoCombo, which simply adds the two scores ShapeTanimoto and ColorTanimoto, was used for the ranking of the pharmacophore-based hit lists. It can take values between 0 and 2. We used the conformations of cocrystallized LXR activators from the PDB entries as query molecules for the alignment of the hit lists produced by the pharmacophores derived from the same PDB entry

LXR Reporter Assay

A bioluminescence assay using the luciferase reporter construct driven by ABCA1 gene promoter was used to quantify the activity of potential LXR modulators. All experimental conditions were exactly as described by us recently, (62) except for overexpressing human LXRβ and using ABCA1 promoter-driven reporter. The induction relative to compound 2 (100%) was determined for all 18 compounds performing three repeats for each experiment at 1 and 25 μM concentration, respectively. Two experiments at 25 μM were not possible due to solubility problems. For four active compounds, additional dose-dependency experiments were performed at five concentrations, and these experiments were evaluated for EC₅₀ estimations.

Supporting Information

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Structures and transactivation assay results of the 18 tested compounds, the comparative analysis of independent pharmacophore and shape-based screening, the test set of compounds used for validation, and the pharmacophore modeling for 3kfc. This material is available free of charge via the Internet at http://pubs.acs.org.

ci300096c_si_001.pdf (705.13 kb)

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Author Information

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Corresponding Author
- Daniela Schuster - Computer-Aided Molecular Design (CAMD) Group and CMBI, Institute of Pharmacy/Pharmaceutical Chemistry, University of Innsbruck, Innrain 80/82, A-6020 Innsbruck, Austria; Email: [email protected]
Authors
- Susanne von Grafenstein - Institute of General, Inorganic and Theoretical Chemistry/Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80/82, A-6020 Innsbruck, Austria
- Judit Mihaly-Bison - Department of Vascular Biology and Thrombosis Research, Medical University of Vienna, Schwarzspanierstrasse 17, A-1090 Wien, Austria
- Gerhard Wolber - Institute of Pharmacy/Pharmaceutical Chemistry, Freie Universitaet Berlin, Koenigin Luise Strasse 2 + 4, D-14195 Berlin, Germany
- Valery N. Bochkov - Department of Vascular Biology and Thrombosis Research, Medical University of Vienna, Schwarzspanierstrasse 17, A-1090 Wien, Austria
- Klaus R. Liedl - Institute of General, Inorganic and Theoretical Chemistry/Theoretical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, Innrain 80/82, A-6020 Innsbruck, Austria
Notes
The authors declare no competing financial interest.

Acknowledgment

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This work was part of the national research network “Drugs from Nature Targeting Inflammation–DNTI“ projects number S107 sponsored by the Austrian Science Fund FWF (subprojects S1072/S10711 and S10709/S10713). Test compounds were provided free of charge by the National Cancer Institute. We thank Dr. Rémy D. Hoffmann, Accelrys SARL Paris, for screening the Derwent WDI database and Patrick Markt, Johannes Kirchmair, Stefan Noha, and Gudrun Spitzer for discussion on methodical issues as well as Judith Rollinger for technical support.

Abbreviations

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LXR	Liver X receptor
LBD	ligand binding domain
DBD	DNA binding domain
HTS	high throughput screening
VS	virtual screening
WDI	world drug index
NCI	National Cancer Institute
EF	enrichment factor
HBA	hydrogen bond acceptor
HBD	hydrogen bond donor
HF	hydrophobic feature
AR	aromatic ring feature
HAF	hydrophobic aromatic feature
sh	shape
Xvols	exclusion volumes
SD standard deviation
RXR	retinoid X receptor

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1
Auwerx, J.; Baulieu, E.; Beato, M.; Becker-Andre, M.; Burbach, P. H.; Camerino, G.; Chambon, P.; Cooney, A.; Dejean, A.; Dreyer, C.; Evans, R. M.; Gannon, F.; Giguere, V.; Gronemeyer, H.; Gustafson, J. A.; Laudet, V.; Lazar, M. A.; Mangelsdorf, D. J.; Milbrandt, J.; Milgrom, E.; Moore, D. D.; O’Malley, B.; Parker, M.; Parker, K.; Perlmann, T.; Pfahl, M.; Rosenfeld, M. G.; Samuels, H.; Schutz, G.; Sladek, F. M.; Stunnenberg, H. G.; Spedding, M.; Thummel, C.; Tsai, M. J.; Umesono, K.; Vennstrom, B.; Wahli, W.; Weinberger, C.; Willson, T. M.; Yamamoto, K. Nucl Receptors Nomenclature, C., A unified nomenclature system for the nuclear receptor superfamily Cell 1999, 97, 161– 163
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Janowski, B. A.; Willy, P. J.; Devi, T. R.; Falck, J. R.; Mangelsdorf, D. J. An oxysterol signalling pathway mediated by the nuclear receptor LXR alpha Nature 1996, 383, 728– 731
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Schultz, J. R.; Tu, H.; Luk, A.; Repa, J. J.; Medina, J. C.; Li, L. P.; Schwendner, S.; Wang, S.; Thoolen, M.; Mangelsdorf, D. J.; Lustig, K. D.; Shan, B. Role of LXRs in control of lipogenesis Genes Dev. 2000, 14, 2831– 2838
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Role of LXRs in control of lipogenesis
Schultz, Joshua R.; Tu, Hua; Luk, Alvin; Repa, Joyce J.; Medina, Julio C.; Li, Leping; Schwendner, Susan; Wang, Shelley; Thoolen, Martin; Mangelsdorf, David J.; Lustig, Kevin D.; Shan, Bei
Genes & Development (2000), 14 (22), 2831-2838CODEN: GEDEEP; ISSN:0890-9369. (Cold Spring Harbor Laboratory Press)
The discovery of oxysterols as the endogenous liver X receptor (LXR) ligands and subsequent gene targeting studies in mice provided strong evidence that LXR plays a central role in cholesterol metab. The identification here of a synthetic, nonsteroidal LXR-selective agonist series represented by T0314407 and T0901317 revealed a novel physiol. role of LXR. Oral administration of T0901317 to mice and hamsters showed that LXR activated the coordinate expression of major fatty acid biosynthetic genes (lipogenesis) and increased plasma triglyceride and phospholipid levels in both species. Complementary studies in cell culture and animals suggested that the increase in plasma lipids occurs via LXR-mediated induction of the sterol regulatory element-binding protein 1 (SREBP-1) lipogenic program.
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Bensinger, S. J.; Tontonoz, P. Integration of metabolism and inflammation by lipid-activated nuclear receptors Nature 2008, 454, 470– 477
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Bensinger, S. J.; Bradley, M. N.; Joseph, S. B.; Zelcer, N.; Janssen, E. M.; Hausner, M. A.; Shih, R.; Parks, J. S.; Edwards, P. A.; Jamieson, B. D.; Tontonoz, P. LXR signaling couples sterol metabolism to proliferation in the acquired immune response Cell 2008, 134, 97– 111
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Joseph, S. B.; Castrillo, A.; Laffitte, B. A.; Mangelsdorf, D. J.; Tontonoz, P. Reciprocal regulation of inflammation and lipid metabolism by liver X receptors Nat. Med. 2003, 9, 213– 219
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6
Reciprocal regulation of inflammation and lipid metabolism by liver X receptors
Joseph, Sean B.; Castrillo, Antonio; Laffitte, Bryan A.; Mangelsdorf, David J.; Tontonoz, Peter
Nature Medicine (New York, NY, United States) (2003), 9 (2), 213-219CODEN: NAMEFI; ISSN:1078-8956. (Nature Publishing Group)
Macrophages have important roles in both lipid metab. and inflammation and are central to the pathogenesis of atherosclerosis. The liver X receptors (LXRs) are established mediators of lipid-inducible gene expression, but their role in inflammation and immunity is unknown. The authors demonstrate here that LXRs and their ligands are neg. regulators of macrophage inflammatory gene expression. Transcriptional profiling of lipopolysaccharide (LPS)-induced macrophages reveals reciprocal LXR-dependent regulation of genes involved in lipid metab. and the innate immune response. In vitro, LXR ligands inhibit the expression of inflammatory mediators such as inducible nitric oxide synthase, cyclooxygenase (COX)-2 and interleukin-6 (IL-6) in response to bacterial infection or LPS stimulation. In vivo, LXR agonists reduce inflammation in a model of contact dermatitis and inhibit inflammatory gene expression in the aortas of atherosclerotic mice. These findings identify LXRs as lipid-dependent regulators of inflammatory gene expression that may serve to link lipid metab. and immune functions in macrophages.
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Kalaany, N. Y.; Mangelsdorf, D. J. LXRs and FXR: The Yin and Yang of cholesterol and fat metabolism Annu. Rev. Physiol. 2006, 68, 159– 191
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8
Collins, J. L.; Fivush, A. M.; Watson, M. A.; Galardi, C. M.; Lewis, M. C.; Moore, L. B.; Parks, D. J.; Wilson, J. G.; Tippin, T. K.; Binz, J. G.; Plunket, K. D.; Morgan, D. G.; Beaudet, E. J.; Whitney, K. D.; Kliewer, S. A.; Willson, T. M. Identification of a nonsteroidal liver X receptor agonist through parallel array synthesis of tertiary amines J. Med. Chem. 2002, 45, 1963– 1966
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Identification of a Nonsteroidal Liver X Receptor Agonist through Parallel Array Synthesis of Tertiary Amines
Collins, Jon L.; Fivush, Adam M.; Watson, Michael A.; Galardi, Cristin M.; Lewis, Michael C.; Moore, Linda B.; Parks, Derek J.; Wilson, Joan G.; Tippin, Tim K.; Binz, Jane G.; Plunket, Kelli D.; Morgan, Daniel G.; Beaudet, Elizabeth J.; Whitney, Karl D.; Kliewer, Steven A.; Willson, Timothy M.
Journal of Medicinal Chemistry (2002), 45 (10), 1963-1966CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
A potent, selective, orally active liver x receptor (LXR) agonist was identified from focused libraries of tertiary amines. GW3965 recruits the steroid receptor coactivator 1 to human LXRα in a cell-free ligand-sensing assay with an EC50 of 125 nM and profiles as a full agonist on hLXRα and hLXRβ in cell-based reporter gene assays with EC50's of 190 and 30 nM, resp. After oral dosing at 10 mg/kg to C57BL/6 mice, GW3965 increased expression of the reverse cholesterol transporter ABCA1 in the small intestine and peripheral macrophages and increased the plasma concns. of HDL cholesterol by 30%. GW3965 will be a valuable chem. tool to investigate the role of LXR in the regulation of reverse cholesterol transport and lipid metab.
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Bradley, M. N.; Hong, C.; Chen, M. Y.; Joseph, S. B.; Wilpitz, D. C.; Wang, X. P.; Lusis, A. J.; Collins, A.; Hseuh, W. A.; Collins, J. L.; Tangirala, R. K.; Tontonoz, P. Ligand activation of LXR beta reverses atherosclerosis and cellular cholesterol overload in mice lacking LXR alpha and apoE J. Clin. Investig. 2007, 117, 2337– 2346
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Ligand activation of LXRβ reverses atherosclerosis and cellular cholesterol overload in mice lacking LXRα and apoE
Bradley, Michelle N.; Hong, Cynthia; Chen, Mingyi; Joseph, Sean B.; Wilpitz, Damien C.; Wang, Xuping; Lusis, Aldons J.; Collins, Allan; Hseuh, Willa A.; Collins, Jon L.; Tangirala, Rajendra K.; Tontonoz, Peter
Journal of Clinical Investigation (2007), 117 (8), 2337-2346CODEN: JCINAO; ISSN:0021-9738. (American Society for Clinical Investigation)
Liver X receptors (LXRs) α and β are transcriptional regulators of cholesterol homeostasis and potential targets for the development of antiatherosclerosis drugs. However, the specific roles of individual LXR isotypes in atherosclerosis and the pharmacol. effects of synthetic agonists remain unclear. Previous work has shown that mice lacking LXRα accumulate cholesterol in the liver but not in peripheral tissues. In striking contrast, we demonstrate here that LXRα-/-apoE-/- mice exhibit extreme cholesterol accumulation in peripheral tissues, a dramatic increase in whole-body cholesterol burden, and accelerated atherosclerosis. The phenotype of these mice suggests that the level of LXR pathway activation in macrophages achieved by LXRβ and endogenous ligand is unable to maintain homeostasis in the setting of hypercholesterolemia. Surprisingly, however, a highly efficacious synthetic agonist was able to compensate for the loss of LXRα. Treatment of LXRα-/-apoE-/- mice with synthetic LXR ligand ameliorates the cholesterol overload phenotype and reduces atherosclerosis. These observations indicate that LXRα has an essential role in maintaining peripheral cholesterol homeostasis in the context of hypercholesterolemia and provide in vivo support for drug development strategies targeting LXRβ.
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Bennett, D. J.; Carswell, E. L.; Cooke, A. J.; Edwards, A. S.; Nimz, O. Design, structure activity relationships and X-ray co-crystallography of non-steroidal LXR agonists Curr. Med. Chem. 2008, 15, 195– 209
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10
Design, structure activity relationships and X-ray co-crystallography of non-steroidal LXR agonists
Bennett, D. J.; Carswell, E. L.; Cooke, A. J.; Edwards, A. S.; Nimz, O.
Current Medicinal Chemistry (2008), 15 (2), 195-209CODEN: CMCHE7; ISSN:0929-8673. (Bentham Science Publishers Ltd.)
A review. The Liver X Receptor (LXR) α and β isoforms are members of the type II nuclear receptor family which function as a heterodimer with the Retinoid X Receptor (RXR). Upon agonist binding, the formation of the LXR/RXR heterodimer takes place and ultimately the regulation of a no. of genes begins. The LXR isoforms share 77% sequence homol., with LXRα having highest expression in liver, intestine, adipose tissue, and macrophages and LXRβ being ubiquitously expressed. The aim of this article is to review the reported-medicinal chem. strategies towards the optimization of novel non-steroidal chemotypes as LXR agonists. An anal. of the structural features important for LXR ligand binding will be given, utilizing both structural activity relation data obtained from LXR assays as well as x-ray co-crystallog. data obtained with LXR ligands and the LXR ligand binding domain (LBD). The x-ray co-crystallog. data anal. will detail the key structural interactions required for LXR binding/agonist activity and reveal the differences obsd. between chemotype classes. It has been postulated that a LXRβ selective compd. may have a beneficial outcome on the lipid profile for a ligand by dissocg. the favorable and unfavorable effects of LXR agonists. While there have been a few examples of compds. showing a modest level of LXRα selectivity, obtaining a potent LXRβ selective compd. has been more challenging. Anal. of the SAR and x-ray co-crystallog. data suggests that the rational design of a LXRβ selective compd. will not be trivial.
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Goodwin, B. J.; Zuercher, W. J.; Collins, J. L. Recent advances in Liver X Receptor biology and chemistry Curr. Top. Med. Chem. 2008, 8, 781– 791
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Recent advances in Liver X Receptor biology and chemistry
Goodwin, Bryan J.; Zuercher, William J.; Collins, Jon L.
Current Topics in Medicinal Chemistry (Sharjah, United Arab Emirates) (2008), 8 (9), 781-791CODEN: CTMCCL; ISSN:1568-0266. (Bentham Science Publishers Ltd.)
A review. The Liver X Receptors LXRα and LXRβ are ligand-activated transcription factors that belong to the nuclear hormone receptor superfamily. Seminal studies with genetic and chem. tools were instrumental in the elucidation of cholesterol metab., gluconeogenesis, inflammation, and lipogenesis as signaling pathways that are controlled by the LXRs. First generation non-steroidal LXR agonists show beneficial effects in multiple animals models of human disease yet have not progressed in the clinic due to deleterious side effects in the liver. Numerous reports have appeared in the recent literature that disclose new LXR signaling pathways and the identification of novel LXR chemotypes that may show improved therapeutic indexes. This review will provide a brief historical perspective but will primarily focus on recent advances in LXR biol. and chem.
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Hu, B.; Quinet, E.; Unwalla, R.; Collini, M.; Jetter, J.; Dooley, R.; Andraka, D.; Nogle, L.; Savio, D.; Halpern, A.; Goos-Nilsson, A.; Wilhelmsson, A.; Nambi, P.; Wrobel, J. Carboxylic acid based quinolines as liver X receptor modulators that have LXR beta receptor binding selectivity Bioorg. Med. Chem. Lett. 2008, 18, 54– 59
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Hu, B.; Unwalla, R.; Collini, M.; Quinet, E.; Feingold, I.; Goos-Nilsson, A.; Wihelmsson, A.; Nambi, P.; Wrobel, J. Discovery and SAR of cinnolines/quinolines as liver X receptor (LXR) agonists with binding selectivity for LXR beta Biorg. Med. Chem. 2009, 17, 3519– 3527
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Discovery and SAR of cinnolines/quinolines as liver X receptor (LXR) agonists with binding selectivity for LXRβ
Hu, Baihua; Unwalla, Raymound; Collini, Michael; Quinet, Elaine; Feingold, Irene; Goos-Nilsson, Annika; Wihelmsson, Anna; Nambi, Ponnal; Wrobel, Jay
Bioorganic & Medicinal Chemistry (2009), 17 (10), 3519-3527CODEN: BMECEP; ISSN:0968-0896. (Elsevier B.V.)
A series of cinnolines/quinolines was prepd. and it was found that 4-phenyl-cinnoline/quinolines with either a 2',3' or 2',5'-disubstituted benzyloxy moiety or the 1-Me-7-indole methoxy moiety on the meta position of the 4-Ph ring showed good binding selectivity for LXRβ over LXRα. The LXRβ binding selective modulators displayed good activity for inducing ABCA1 gene expression in J774 macrophage cell line and poor efficacy in the LXRα Gal4 functional assay. 26, 37 and 41 were examd. for their ability to induce SREBP-1c gene expression in Huh-7 liver cell line and they were weak partial agonists.
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Wrobel, J.; Steffan, R.; Bowen, S. M.; Magolda, R.; Matelan, E.; Unwalla, R.; Basso, M.; Clerin, V.; Gardell, S. J.; Nambi, P.; Quinet, E.; Reminick, J. I.; Vlasuk, G. P.; Wang, S.; Feingold, I.; Huselton, C.; Bonn, T.; Farnegardh, M.; Hansson, T.; Nilsson, A. G.; Wilhelmsson, A.; Zamaratski, E.; Evans, M. J. Indazole-based liver X receptor (LXR) modulators with maintained atherosclerotic lesion reduction activity but diminished stimulation of hepatic triglyceride synthesis J. Med. Chem. 2008, 51, 7161– 7168
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Fievet, C.; Staels, B. Liver X receptor modulators: Effects on lipid metabolism and potential use in the treatment of atherosclerosis Biochem. Pharmacol. 2009, 77, 1316– 1327
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Calkin, A. C.; Tontonoz, P. Liver X receptor signaling pathways and atherosclerosis Arterioscler. Thromb. Vasc. Biol. 2010, 30, 1513– 1518
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Liver X Receptor Signaling Pathways and Atherosclerosis
Calkin, Anna C.; Tontonoz, Peter
Arteriosclerosis, Thrombosis, and Vascular Biology (2010), 30 (8), 1513-1518CODEN: ATVBFA; ISSN:1079-5642. (Lippincott Williams & Wilkins)
A review. First discovered as orphan receptors, liver X receptors (LXRs) were subsequently identified as the nuclear receptor target of the cholesterol metabolites, oxysterols. There are 2 LXR receptors encoded by distinct genes: LXRα is most highly expressed in the liver, adipose, kidney, adrenal tissues, and macrophages and LXRβ is ubiquitously expressed. Despite differential tissue distribution, these isoforms have 78% homol. in their ligand-binding domain and appear to respond to the same endogenous ligands. Work over the past 10 years has shown that the LXR pathway regulates lipid metab. and inflammation via both the induction and repression of target genes. Given the importance of cholesterol regulation and inflammation in the development of cardiovascular disease, it is not surprising that activation of the LXR pathway attenuates various mechanisms underlying atherosclerotic plaque development. In this brief review, we will discuss the impact of the LXR pathway on both cholesterol metab. and atherosclerosis.
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Zuercher, W. J.; Buckholz, R. G.; Campobasso, N.; Collins, J. L.; Galardi, C. M.; Gampe, R. T.; Hyatt, S. M.; Merrihew, S. L.; Moore, J. T.; Oplinger, J. A.; Reid, P. R.; Spearing, P. K.; Stanley, T. B.; Stewart, E. L.; Willson, T. M. Discovery of tertiary sulfonamides as potent liver X receptor antagonists J. Med. Chem. 2010, 53, 3412– 3416
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Joseph, S. B.; Bradley, M. N.; Castrillo, A.; Bruhn, K. W.; Mak, P. A.; Pei, L. M.; Hogenesch, J.; O’Connell, R. M.; Cheng, G. H.; Saez, E.; Miller, J. F.; Tontonoz, P. LXR-dependent gene expression is important for macrophage survival and the innate immune response Cell 2004, 119, 299– 309
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LXR-dependent gene expression is important for macrophage survival and the innate immune response
Joseph, Sean B.; Bradley, Michelle N.; Castrillo, Antonio; Bruhn, Kevin W.; Mak, Puiying A.; Pei, Liming; Hogenesch, John; O'Connell, Ryan M.; Cheng, Genhong; Saez, Enrique; Miller, Jeffery F.; Tontonoz, Peter
Cell (Cambridge, MA, United States) (2004), 119 (2), 299-309CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
The liver X receptors (LXRs) are nuclear receptors with established roles in the regulation of lipid metab. We now show that LXR signaling not only regulates macrophage cholesterol metab. but also impacts antimicrobial responses. Mice lacking LXRs are highly susceptible to infection with the intracellular bacteria Listeria monocytogenes (LM). Bone marrow transplant studies point to altered macrophage function as the major determinant of susceptibility. LXR-null macrophages undergo accelerated apoptosis when challenged with LM and exhibit defective bacterial clearance in vivo. These defects result, at least in part, from loss of regulation of the antiapoptotic factor SPα, a direct target for regulation by LXRα. Expression of LXRα or SPα in macrophages inhibits apoptosis in the setting of LM infection. Our results demonstrate that LXR-dependent gene expression plays an unexpected role in innate immunity and suggest that common nuclear receptor pathways mediate macrophage responses to modified lipoproteins and intracellular pathogens.
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Villablanca, E. J.; Raccosta, L.; Zhou, D.; Fontana, R.; Maggioni, D.; Negro, A.; Sanvito, F.; Ponzoni, M.; Valentinis, B.; Bregni, M.; Prinetti, A.; Steffensen, K. R.; Sonnino, S.; Gustafsson, J. A.; Doglioni, C.; Bordignon, C.; Traversari, C.; Russo, V. Tumor-mediated liver X receptor-alpha activation inhibits CC chemokine receptor-7 expression on dendritic cells and dampens antitumor responses Nat. Med. 2010, 16, 98– 105
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Tumor-mediated liver X receptor-α activation inhibits CC chemokine receptor-7 expression on dendritic cells and dampens antitumor responses
Villablanca, Eduardo J.; Raccosta, Laura; Zhou, Dan; Fontana, Raffaella; Maggioni, Daniela; Negro, Aurora; Sanvito, Francesca; Ponzoni, Maurilio; Valentinis, Barbara; Bregni, Marco; Prinetti, Alessandro; Steffensen, Knut R.; Sonnino, Sandro; Gustafsson, Jan-Ake; Doglioni, Claudio; Bordignon, Claudio; Traversari, Catia; Russo, Vincenzo
Nature Medicine (New York, NY, United States) (2010), 16 (1), 98-105CODEN: NAMEFI; ISSN:1078-8956. (Nature Publishing Group)
Sterol metab. has recently been linked to innate and adaptive immune responses through liver X receptor (LXR) signaling. Whether products of sterol metab. interfere with antitumor responses is currently unknown. Dendritic cells (DCs) initiate immune responses, including antitumor activity after their CC chemokine receptor-7 (CCR7)-dependent migration to lymphoid organs. Here the authors report that human and mouse tumors produce LXR ligands that inhibit CCR7 expression on maturing DCs and, therefore, their migration to lymphoid organs. In agreement with this observation, the authors detected CD83+CCR7- DCs within human tumors. Mice injected with tumors expressing the LXR ligand-inactivating enzyme sulfotransferase 2B1b (SULT2B1b) successfully controlled tumor growth by regaining DC migration to tumor-draining lymph nodes and by developing overt inflammation within tumors. The control of tumor growth was also obsd. in chimeric mice transplanted with bone marrow from mice lacking the gene encoding LXR-α (Nr1h3-/- mice). Thus, the authors show a new mechanism of tumor immunoescape involving products of cholesterol metab. The manipulation of this pathway could restore antitumor immunity in individuals with cancer.
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Zelcer, N.; Khanlou, N.; Clare, R.; Jiang, Q.; Reed-Geaghan, E. G.; Landreth, G. E.; Vinters, H. V.; Tontonoz, P. Attenuation of neuroinflammation and Alzheimer’s disease pathology by liver x receptors Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 10601– 10606
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Fitz, N. F.; Cronican, A.; Pham, T.; Fogg, A.; Fauq, A. H.; Chapman, R.; Lefterov, I.; Koldamova, R. Liver X receptor agonist treatment ameliorates amyloid pathology and memory deficits caused by high-fat diet in APP23 mice J. Neurosci. 2010, 30, 6862– 6872
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Liver X receptor agonist treatment ameliorates amyloid pathology and memory deficits caused by high-fat diet in APP23 mice
Fitz, Nicholas F.; Cronican, Andrea; Pham, Tam; Fogg, Allison; Fauq, Abdul H.; Chapman, Robert; Lefterov, Iliya; Koldamova, Radosveta
Journal of Neuroscience (2010), 30 (20), 6862-6872CODEN: JNRSDS; ISSN:0270-6474. (Society for Neuroscience)
High-fat diet and certain dietary patterns are assocd. with higher incidence of sporadic Alzheimer's disease (AD) and cognitive decline. However, no specific therapy has been suggested to ameliorate the neg. effects of high fat/high cholesterol levels on cognition and amyloid pathol. Here we show that in 9-mo-old APP23 mice, a high-fat/high-cholesterol (HF) diet provided for 4 mo exacerbates the AD phenotype evaluated by behavioral, morphol., and biochem. assays. To examine the therapeutic potential of liver X receptor (LXR) ligands, APP23 mice were fed HF diet supplemented with synthetic LXR agonist T0901317 (T0). Our results demonstrate that LXR ligand treatment causes a significant redn. of memory deficits obsd. during both acquisition and retention phases of the Morris water maze. Moreover, the effects of T0 on cognition correlate with AD-like morphol. and biochem. parameters. We found a significant decrease in amyloid plaque load, insol. Aβ and sol. Aβ oligomers. In vitro expts. with primary glia demonstrate that Abca1 is essential for the proper lipidation of ApoE and mediates the effects of T0 on Aβ degrdn. by microglia. Microdialysis expts. performed on awake freely moving mice showed that T0 decreased Aβ levels in the interstitial fluid of the hippocampus, supporting the conclusion that this treatment increases Aβ clearance. The data presented conclusively shows that LXR activation in the context of a metabolic challenge has crit. effects on AD phenotype progression by attenuating Aβ deposition and facilitating its clearance.
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Baranowski, M. Biological role of liver X receptors J. Physiol. Pharmacol. 2008, 59, 31– 55
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Biological role of liver X receptors
Baranowski M
Journal of physiology and pharmacology : an official journal of the Polish Physiological Society (2008), 59 Suppl 7 (), 31-55 ISSN:.
Liver X receptors (LXRs) are ligand-activated transcription factors of the nuclear receptor superfamily. There are two LXR isoforms termed alpha and beta which upon activation form heterodimers with retinoid X receptor and bind to LXR response element found in the promoter region of the target genes. Their endogenous agonists include a variety of oxidized cholesterol derivatives referred to as oxysterols. In the recent years LXRs have been characterized as key transcriptional regulators of lipid and carbohydrate metabolism. LXRs were shown to function as sterol sensors protecting the cells from cholesterol overload by stimulating reverse cholesterol transport and activating its conversion to bile acids in the liver. This finding led to identification of LXR agonists as potent antiatherogenic agents in rodent models of atherosclerosis. However, first-generation LXR activators were also shown to stimulate lipogenesis via sterol regulatory element binding protein-1c leading to liver steatosis and hypertriglyceridemia. Despite their lipogenic action, LXR agonists possess antidiabetic properties. LXR activation normalizes glycemia and improves insulin sensitivity in rodent models of type 2 diabetes and insulin resistance. Antidiabetic action of LXR agonists is thought to result predominantly from suppression of hepatic gluconeogenesis. However, recent studies suggest that LXR activation may also enhance peripheral glucose uptake. The purpose of this review is to summarize the present state of knowledge on the physiological and pathophysiological implications of LXRs with the special consideration of their role in lipid and carbohydrate metabolism and associated diseases.
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Berman, H.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.; Weissig, H.; Shindyalov, I.; Bourne, P. The Protein Data Bank Nucleic Acids Res. 2000, 28, 235– 42
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The Protein Data Bank
Berman, Helen M.; Westbrook, John; Feng, Zukang; Gilliland, Gary; Bhat, T. N.; Weissig, Helge; Shindyalov, Ilya N.; Bourne, Philip E.
Nucleic Acids Research (2000), 28 (1), 235-242CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
The Protein Data Bank (PDB; http://www.rcsb.org/pdb/)is the single worldwide archive of structural data of biol. macromols. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
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Berman, H.; Henrick, K.; Nakamura, H. Announcing the worldwide Protein Data Bank Nat. Struct. Mol. Biol. 2003, 10, 980– 980
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Announcing the worldwide Protein Data Bank
Berman, Helen; Henrick, Kim; Nakamura, Haruki
Nature Structural Biology (2003), 10 (12), 980CODEN: NSBIEW; ISSN:1072-8368. (Nature Publishing Group)
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Farnegardh, M.; Bonn, T.; Sun, S.; Ljunggren, J.; Ahola, H.; Wilhelmsson, A.; Gustafsson, J. A.; Carlquist, M. The three-dimensional structure of the liver X receptor beta reveals a flexible ligand-binding pocket that can accommodate fundamentally different ligands J. Biol. Chem. 2003, 278, 38821– 38828
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The three-dimensional structure of the liver X receptor beta reveals a flexible ligand-binding pocket that can accommodate fundamentally different ligands
Farnegardh Mathias; Bonn Tomas; Sun Sherry; Ljunggren Jan; Ahola Harri; Wilhelmsson Anna; Gustafsson Jan-Ake; Carlquist Mats
The Journal of biological chemistry (2003), 278 (40), 38821-8 ISSN:0021-9258.
The structures of the liver X receptor LXRbeta (NR1H2) have been determined in complexes with two synthetic ligands, T0901317 and GW3965, to 2.1 and 2.4 A, respectively. Together with its isoform LXRalpha (NR1H3) it regulates target genes involved in metabolism and transport of cholesterol and fatty acids. The two LXRbeta structures reveal a flexible ligand-binding pocket that can adjust to accommodate fundamentally different ligands. The ligand-binding pocket is hydrophobic but with polar or charged residues at the two ends of the cavity. T0901317 takes advantage of this by binding to His-435 close to H12 while GW3965 orients itself with its charged group in the opposite direction. Both ligands induce a fixed "agonist conformation" of helix H12 (also called the AF-2 domain), resulting in a transcriptionally active receptor.
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Washburn, D. G.; Hoang, T. H.; Campobasso, N.; Smallwood, A.; Parks, D. J.; Webb, C. L.; Frank, K. A.; Nord, M.; Duraiswami, C.; Evans, C.; Jaye, M.; Thompson, S. K. Synthesis and SAR of potent LXR agonists containing an indole pharmacophore Bioorg. Med. Chem. Lett. 2009, 19, 1097– 1100
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Chao, E. Y.; Caravella, J. A.; Watson, M. A.; Campobasso, N.; Ghisletti, S.; Billin, A. N.; Galardi, C.; Wang, P.; Laffitte, B. A.; Lannone, M. A.; Goodwin, B. J.; Nichols, J. A.; Parks, D. J.; Stewart, E.; Wiethe, R. W.; Williams, S. P.; Smallwood, A.; Pearce, K. H.; Glass, C. K.; Willson, T. M.; Zuercher, W. J.; Collins, J. L. Structure-guided design of N-phenyl tertiary amines as transrepression-selective liver X receptor modulators with anti-inflammatory activity J. Med. Chem. 2008, 51, 5758– 5765
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Structure-Guided Design of N-Phenyl Tertiary Amines as Transrepression-Selective Liver X Receptor Modulators with Anti-Inflammatory Activity
Chao, Esther Y.; Caravella, Justin A.; Watson, Mike A.; Campobasso, Nino; Ghisletti, Serena; Billin, Andrew N.; Galardi, Cristin; Wang, Ping; Laffitte, Bryan A.; Iannone, Marie A.; Goodwin, Bryan J.; Nichols, Jason A.; Parks, Derek J.; Stewart, Eugene; Wiethe, Robert W.; Williams, Shawn P.; Smallwood, Angela; Pearce, Kenneth H.; Glass, Christopher K.; Willson, Timothy M.; Zuercher, William J.; Collins, Jon L.
Journal of Medicinal Chemistry (2008), 51 (18), 5758-5765CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
A cocrystal structure of T1317 (3) bound to hLXRβ was utilized in the design of a series of substituted N-Ph tertiary amines. Profiling in binding and functional assays led to the identification of LXR modulator GSK9772 (I) as a high-affinity LXRβ ligand (IC50 = 30 nM) that shows sepn. of anti-inflammatory and lipogenic activities in human macrophage and liver cell lines, resp. A cocrystal structure of the structurally related analog 19 bound to LXRβ reveals regions within the receptor that can affect receptor modulation through ligand modification. Mechanistic studies demonstrate that 20 is greater than 10-fold selective for LXR-mediated transrepression of proinflammatory gene expression vs. transactivation of lipogenic signaling pathways, thus providing an opportunity for the identification of LXR modulators with improved therapeutic indexes.
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Jaye, M. C.; Krawiec, J. A.; Campobasso, N.; Smallwood, A.; Qiu, C. Y.; Lu, Q.; Kerrigan, J. J.; Alvaro, M. D. L.; Laffitte, B.; Liu, W. S.; Marino, J. P.; Meyer, C. R.; Nichols, J. A.; Parks, D. J.; Perez, P.; Sarov-Blat, L.; Seepersaud, S. D.; Steplewski, K. M.; Thompson, S. K.; Wang, P.; Watson, M. A.; Webb, C. L.; Haigh, D.; Caravella, J. A.; Macphee, C. H.; Willson, T. M.; Collins, J. L. Discovery of substituted maleimides as liver X receptor agonists and determination of a ligand-bound crystal structure J. Med. Chem. 2005, 48, 5419– 5422
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Discovery of Substituted Maleimides as Liver X Receptor Agonists and Determination of a Ligand-Bound Crystal Structure
Jaye, Michael C.; Krawiec, John A.; Campobasso, Nino; Smallwood, Angela; Qiu, Chunyan; Lu, Quinn; Kerrigan, John J.; De Los Frailes Alvaro, Maite; Laffitte, Bryan; Liu, Wu-Schyong; Marino, Joseph P., Jr.; Meyer, Craig R.; Nichols, Jason A.; Parks, Derek J.; Perez, Paloma; Sarov-Blat, Lea; Seepersaud, Sheila D.; Steplewski, Klaudia M.; Thompson, Scott K.; Wang, Ping; Watson, Mike A.; Webb, Christine L.; Haigh, David; Caravella, Justin A.; Macphee, Colin H.; Willson, Timothy M.; Collins, Jon L.
Journal of Medicinal Chemistry (2005), 48 (17), 5419-5422CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
Substituted 3-(phenylamino)-1H-pyrrole-2,5-diones were identified from a high throughput screen as inducers of human ATP binding cassette transporter A1 expression. Mechanism of action studies led to the identification of GSK3987 (I) as an LXR ligand. I recruits the steroid receptor coactivator-1 to human LXRα and LXRβ with EC50s of 40 nM, profiles as an LXR agonist in functional assays, and activates LXR though a mechanism that is similar to first generation LXR agonists.
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Kher, S.; Lake, K.; Sircar, I.; Pannala, M.; Bakir, F.; Zapf, J.; Xu, K.; Zhang, S. H.; Liu, J. P.; Morera, L.; Sakurai, N.; Jack, R.; Cheng, J. F. 2-Aryl-N-acyl indole derivatives as liver X receptor (LXR) agonists Bioorg. Med. Chem. Lett. 2007, 17, 4442– 4446
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2-Aryl-N-acyl indole derivatives as liver X receptor (LXR) agonists
Kher, Sunil; Lake, Kirk; Sircar, Ila; Pannala, Madhavi; Bakir, Farid; Zapf, James; Xu, Kui; Zhang, Shao-Hui; Liu, Juping; Morera, Lisa; Sakurai, Naoki; Jack, Rick; Cheng, Jie-Fei
Bioorganic & Medicinal Chemistry Letters (2007), 17 (16), 4442-4446CODEN: BMCLE8; ISSN:0960-894X. (Elsevier Ltd.)
Structure-activity relationship studies on a series of Boc-indole derivs. as LXR agonists are described. Compd. 1 (I) was identified as an LXR agonist through structure-based virtual screening followed by high-throughput gene profiling. Replacement of the indan linker portion in 1 with an open-chain linker resulted in compds. with similar or improved in vitro potency and cellular functional activity. The Boc group at the N-1 position of the indole moiety can be replaced with a benzoyl group. The SAR studies led to the identification of compd. 8, a potent LXRβ agonist with an EC50 of 12 nM in the cofactor recruitment assay.
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Cheng, J. F.; Zapf, J.; Takedomi, K.; Fukushima, C.; Ogiku, T.; Zhang, S. H.; Yang, G.; Sakurai, N.; Barbosa, M.; Jack, R.; Xu, K. Combination of virtual screening and high throughput gene profiling for identification of novel liver X receptor modulators J. Med. Chem. 2008, 51, 2057– 2061
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Ghemtio, L.; Devignes, M. D.; Smail-Tabbone, M.; Souchet, M.; Leroux, V.; Maigret, B. Comparison of three preprocessing filters efficiency in virtual screening: Identification of new putative LXR beta regulators as a test case J. Chem. Inf. Model. 2010, 50, 701– 715
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Comparison of Three Preprocessing Filters Efficiency in Virtual Screening: Identification of New Putative LXRβ Regulators As a Test Case
Ghemtio, Leo; Devignes, Marie-Dominique; Smail-Tabbone, Malika; Souchet, Michel; Leroux, Vincent; Maigret, Bernard
Journal of Chemical Information and Modeling (2010), 50 (5), 701-715CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
In silico screening methodologies are widely recognized as efficient approaches in early steps of drug discovery. However, in the virtual high-throughput screening (VHTS) context, where hit compds. are searched among millions of candidates, three-dimensional comparison techniques and knowledge discovery from databases should offer a better efficiency to finding novel drug leads than those of computationally expensive mol. dockings. Therefore, the present study aims at developing a filtering methodol. to efficiently eliminate unsuitable compds. in VHTS process. Several filters are evaluated in this paper. The first two are structure-based and rely on either geometrical docking or pharmacophore depiction. The third filter is ligand-based and uses knowledge-based and fingerprint similarity techniques. These filtering methods were tested with the Liver X Receptor (LXR) as a target of therapeutic interest, as LXR is a key regulator in maintaining cholesterol homeostasis. The results show that the three considered filters are complementary so that their combination should generate consistent compd. lists of potential hits.
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Zhao, W.; Gu, Q.; Wang, L.; Ge, H.; Li, J.; Xu, J. Three-dimensional pharmacophore modeling of liver-X receptor agonists J. Chem. Inf. Model. 2011, 51, 2147– 2155
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Three-Dimensional Pharmacophore Modeling of Liver-X Receptor Agonists
Zhao, Wenxia; Gu, Qiong; Wang, Ling; Ge, Hu; Li, Jiabo; Xu, Jun
Journal of Chemical Information and Modeling (2011), 51 (9), 2147-2155CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
High cholesterol levels contribute to hyperlipidemia. Liver X receptors (LXRs) are the drug targets. LXRs regulate the cholesterol absorption, biosynthesis, transportation, and metab. Novel agonists of LXR, esp. LXRβ, are attractive solns. for treating hyperlipidemia. In order to discover novel LXRβ agonists, a three-dimensional pharmacophore model was built based upon known LXRβ agonists. The model was validated with a test set, a virtual screening expt., and the FlexX docking approach. Results show that the model is capable of predicting a LXRβ agonist activity. Ligand-based virtual screening results can be refined by crosslinking by structure-based approaches. This is because two ligands that are mapped in the same way to the same pharmacophore model may have significantly different binding behaviors in the receptor's binding pocket. This paper reports our approach to identify reliable pharmacophore models through combining both ligand- and structure-based approaches.
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Beautrait, A.; Leroux, V.; Chavent, M.; Ghemtio, L.; Devignes, M. D.; Smaiel-Tabbone, M.; Cai, W.; Shao, X.; Moreau, G.; Bladon, P.; Yao, J.; Maigret, B. Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment J. Mol. Model. 2008, 14, 135– 148
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Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment
Beautrait, Alexandre; Leroux, Vincent; Chavent, Matthieu; Ghemtio, Leo; Devignes, Marie-Dominique; Smail-Tabbone, Malika; Cai, Wensheng; Shao, Xuegang; Moreau, Gilles; Bladon, Peter; Yao, Jianhua; Maigret, Bernard
Journal of Molecular Modeling (2008), 14 (2), 135-148CODEN: JMMOFK; ISSN:0948-5023. (Springer GmbH)
Numerous methods are available for use as part of a virtual screening strategy but, as yet, no single method is able to guarantee both a level of confidence comparable to exptl. screening and a level of computing efficiency that could drastically cut the costs of early phase drug discovery campaigns. Here, we present VSM-G (virtual screening manager for computational grids), a virtual screening platform that combines several structure-based drug design tools. VSM-G aims to be as user-friendly as possible while retaining enough flexibility to accommodate other in silico techniques as they are developed. In order to illustrate VSM-G concepts, we present a proof-of-concept study of a fast geometrical matching method based on spherical harmonics expansions surfaces. This technique is implemented in VSM-G as the first module of a multiple-step sequence tailored for high-throughput expts. We show that, using this protocol, notable enrichment of the input mol. database can be achieved against a specific target, here the liver-X nuclear receptor. The benefits, limitations and applicability of the VSM-G approach are discussed. Possible improvements of both the geometrical matching technique and its implementation within VSM-G are suggested.
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Leach, A. R.; Gillet, V. J.; Lewis, R. A.; Taylor, R. Three-dimensional pharmacophore methods in drug discovery J. Med. Chem. 2010, 53, 539– 558
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Three-Dimensional Pharmacophore Methods in Drug Discovery
Leach, Andrew R.; Gillet, Valerie J.; Lewis, Richard A.; Taylor, Robin
Journal of Medicinal Chemistry (2010), 53 (2), 539-558CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
A review. In the first part of this Perspective the authors provide an overview of the computational 3D pharmacophore methods most commonly used in drug discovery. The authors focus in particular on the key problem of pharmacophore elucidation: the identification from a set of active mols. and their biol. activities of the key common features and their relative orientations (also called pharmacophore mapping). In the second part the authors reflect on the challenges in this field and provide some thoughts on future directions. The authors' primary goal is to provide the interested reader with a fair assessment of the current state-of-the-art in this field with an emphasis on the methods and software that in the authors' experience are most widely used in real drug discovery projects. The authors will cover both the practical aspects and some of the inherent limitations of such methods.
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Langer, T. Pharmacophores in drug research Mol. Inform. 2010, 29, 470– 475
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Pharmacophores in Drug Research
Langer, Thierry
Molecular Informatics (2010), 29 (6-7), 470-475CODEN: MIONBS; ISSN:1868-1743. (Wiley-VCH Verlag GmbH & Co. KGaA)
A review. The pharmacophore concept in modern drug research is highlighted and the most important use examples and success stories are reviewed. These include papers from method development as well as from application areas. As indicated by the no. of publications available, the pharmacophore approach has proven to be extremely useful as interface between medicinal and computational chem., both in virtual screening and library design for efficient hit discovery, but also in the optimization of lead compds. to clin. candidates. Recent studies focus on the usage of parallel screening using pharmacophore models for bio-activity profiling and early stage risk assessment of potential side effects and toxicity due to interaction of drug candidates with anti-targets.
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Wolber, G.; Langer, T. LigandScout: 3-D pharmacophores derived from protein-bound Ligands and their use as virtual screening filters J. Chem. Inf. Model. 2005, 45, 160– 169
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LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters
Wolber Gerhard; Langer Thierry
Journal of chemical information and modeling (2005), 45 (1), 160-9 ISSN:1549-9596.
From the historically grown archive of protein-ligand complexes in the Protein Data Bank small organic ligands are extracted and interpreted in terms of their chemical characteristics and features. Subsequently, pharmacophores representing ligand-receptor interaction are derived from each of these small molecules and its surrounding amino acids. Based on a defined set of only six types of chemical features and volume constraints, three-dimensional pharmacophore models are constructed, which are sufficiently selective to identify the described binding mode and are thus a useful tool for in-silico screening of large compound databases. The algorithms for ligand extraction and interpretation as well as the pharmacophore creation technique from the automatically interpreted data are presented and applied to a rhinovirus capsid complex as application example.
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OEChem, version 1.7.0; OpenEye Scientific Software, I., Santa Fe, NM, USA; www.eyesopen.com, 2009.
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Grant, J. A.; Gallardo, M. A.; Pickup, B. T. A fast method of molecular shape comparison: A simple application of a Gaussian description of molecular shape J. Comput. Chem. 1996, 17, 1653– 1666
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A fast method of molecular shape comparison: a simple application of a Gaussian description of molecular shape
Grant, J. A.; Gallard, M. A.; Pickup, B. T.
Journal of Computational Chemistry (1996), 17 (14), 1653-1666CODEN: JCCHDD; ISSN:0192-8651. (Wiley)
A gaussian description of mol. shape is used to compare the shapes of two mols. by anal. optimizing their vol. intersection. The method is applied to predict the relative orientation of ligand series binding to the proteins, thrombin, HIV protease, and thermolysin. The method is also used to quantify the degree of chirality of asym. mols. and to investigate the chirality of biphenyl and the amino acids. The shape comparison method uses the newly described shape multipoles that can also be used to describe the inherent shape of mols. Some results of calcd. shape quadrupoles are given for the ligands used in this work.
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Williams, S.; Bledsoe, R. K.; Collins, J. L.; Boggs, S.; Lambert, M. H.; Miller, A. B.; Moore, J.; McKee, D. D.; Moore, L.; Nichols, J.; Parks, D.; Watson, M.; Wisely, B.; Willson, T. M. X-ray crystal structure of the liver X receptor beta ligand binding domain - Regulation by a histidine-tryptophan switch J. Biol. Chem. 2003, 278, 27138– 27143
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Ratni, H.; Blum-Kaelin, D.; Dehmlow, H.; Hartman, P.; Jablonski, P.; Masciadri, R.; Maugeais, C.; Patiny-Adam, A.; Panday, N.; Wright, M. Discovery of tetrahydro-cyclopenta[b]indole as selective LXRs modulator Bioorg. Med. Chem. Lett. 2009, 19, 1654– 1657
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Markt, P.; Petersen, R.; Flindt, E.; Kristiansen, K.; Kirchmair, J.; Spitzer, G.; Distinto, S.; Schuster, D.; Wolber, G.; Laggner, C.; Langer, T. Discovery of novel PPAR ligands by a virtual screening approach based on pharmacophore modeling, 3D shape, and electrostatic similarity screening J. Med. Chem. 2008, 51, 6303– 17
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Discovery of Novel PPAR Ligands by a Virtual Screening Approach Based on Pharmacophore Modeling, 3D Shape, and Electrostatic Similarity Screening
Markt, Patrick; Petersen, Rasmus K.; Flindt, Esben N.; Kristiansen, Karsten; Kirchmair, Johannes; Spitzer, Gudrun; Distinto, Simona; Schuster, Daniela; Wolber, Gerhard; Laggner, Christian; Langer, Thierry
Journal of Medicinal Chemistry (2008), 51 (20), 6303-6317CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
Peroxisome proliferator-activated receptors (PPARs) are important targets for drugs used in the treatment of atherosclerosis, dyslipidemia, obesity, type 2 diabetes, and other diseases caused by abnormal regulation of the glucose and lipid metab. We applied a virtual screening workflow based on a combination of pharmacophore modeling with 3D shape and electrostatic similarity screening techniques to discover novel scaffolds for PPAR ligands. From the resulting 10 virtual screening hits, five tested pos. in human PPAR ligand-binding domain (hPPAR-LBD) transactivation assays and showed affinities for PPAR in a competitive binding assay. Compds. 5, 7, and 8 were identified as PPAR-α agonists, whereas compds. 2 and 9 showed agonistic activity for hPPAR-γ. Moreover, compd. 9 was identified as a PPAR-δ antagonist. These results demonstrate that our virtual screening protocol is able to enrich novel scaffolds for PPAR ligands that could be useful for drug development in the area of atherosclerosis, dyslipidemia, and type 2 diabetes.
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Noha, S. M.; Atanasov, A. G.; Schuster, D.; Markt, P.; Fakhrudin, N.; Heiss, E. H.; Schrammel, O.; Rollinger, J. M.; Stuppner, H.; Dirsch, V. M.; Wolber, G. Discovery of a novel IKK-beta inhibitor by ligand-based virtual screening techniques Bioorg. Med. Chem. Lett. 2011, 21, 577– 583
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Fakhrudin, N.; Ladurner, A.; Atanasov, A. G.; Heiss, E. H.; Baumgartner, L.; Markt, P.; Schuster, D.; Ellmerer, E. P.; Wolber, G.; Rollinger, J. M.; Stuppner, H.; Dirsch, V. M. Computer-aided discovery, validation, and mechanistic characterization of novel neolignan activators of peroxisome proliferator-activated receptor gamma Mol. Pharmacol. 2010, 77, 559– 566
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Waltenberger, B.; Wiechmann, K.; Bauer, J.; Markt, P.; Noha, S. M.; Wolber, G.; Rollinger, J. M.; Werz, O.; Schuster, D.; Stuppner, H. Pharmacophore modeling and virtual xcreening for novel acidic inhibitors of microsomal prostaglandin E-2 synthase-1 (mPGES-1) J. Med. Chem. 2011, 54, 3163– 3174
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Schuster, D.; Waltenberger, B.; Kirchmair, J.; Distinto, S.; Markt, P.; Stuppner, H.; Rollinger, J. M.; Wolber, G. Predicting cyclooxygenase inhibition by three-dimensional pharmacophoric profiling. Part I: model generation, validation and applicability in ethnopharmacology Mol. Inform. 2010, 29, 75– 86
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Predicting cyclooxygenase inhibition by three-dimensional pharmacophoric profiling. Part I: model generation, validation and applicability in ethnopharmacology
Schuster, Daniela; Waltenberger, Birgit; Kirchmair, Johannes; Distinto, Simona; Markt, Patrick; Stuppner, Hermann; Rollinger, Judith M.; Wolber, Gerhard
Molecular Informatics (2010), 29 (1-2), 75-86CODEN: MIONBS; ISSN:1868-1743. (Wiley-VCH Verlag GmbH & Co. KGaA)
3D pharmacophore modeling has evolved as an established and state-of-the-art method for performing insilico predictions of biol. activity. Using one single model is limited to single binding modes, while the combination of several models bears a broader application scope. We demonstrate the generation of a complete and predictive 3D model set for cyclooxygenase 1 and 2 inhibitors, along with a selection and validation protocol optimized for parallel virtual screening. This model set was applied to explain the cyclooxygenase activity of an ethnopharmacol. known mixt. of natural products, the Thai traditional medicine "Prasaplai". Results show that rationalizing natural product activity by modern in-silico approaches is promising and can be tremendously useful in the identification of the mechanisms of action for known biol. effects of complex herbal remedies.
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Schuster, D. 3D pharmacophores as tools for activity profiling Drug Discovery Today: Technol. 2010, 7, 205– 211
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Bernotas, R. C.; Singhaus, R. R.; Kaufman, D. H.; Travins, J. M.; Ullrich, J. W.; Unwalla, R.; Quinet, E.; Evans, M.; Nambi, P.; Olland, A.; Kauppi, B.; Wilhelmsson, A.; Goos-Nilsson, A.; Wrobel, J. 4-(3-Aryloxyaryl)quinoline sulfones are potent liver X receptor agonists Bioorg. Med. Chem. Lett. 2010, 20, 209– 212
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Spencer, T. A.; Li, D. S.; Russel, J. S.; Collins, J. L.; Bledsoe, R. K.; Consler, T. G.; Moore, L. B.; Galardi, C. M.; McKee, D. D.; Moore, J. T.; Watson, M. A.; Parks, D. J.; Lambert, M. H.; Willson, T. M. Pharmacophore analysis of the nuclear oxysterol receptor LXR alpha J. Med. Chem. 2001, 44, 886– 897
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Yang, C. D.; McDonald, J. G.; Patel, A.; Zhang, Y.; Umetani, M.; Xu, F.; Westover, E. J.; Covey, D. F.; Mangelsdorf, D. J.; Cohen, J. C.; Hobbs, H. H. Sterol intermediates from cholesterol biosynthetic pathway as liver X receptor ligands J. Biol. Chem. 2006, 281, 27816– 27826
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Molteni, V.; Li, X.; Nabakka, J.; Liang, F.; Wityak, J.; Koder, A.; Vargas, L.; Romeo, R.; Mitro, N.; Mak, P. A.; Seidel, M.; Haslam, J. A.; Chow, D.; Tuntland, T.; Spalding, T. A.; Brock, A.; Bradley, M.; Castrillo, A.; Tontonoz, P.; Saez, E. N-acylthiadiazolines, a new class of liver x receptor agonists with selectivity for LXR beta J. Med. Chem. 2007, 50, 4255– 4259
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Li, L. P.; Liu, J. W.; Zhu, L. S.; Cutler, S.; Hasegawa, H.; Shan, B.; Medina, J. C. Discovery and optimization of a novel series of liver X receptor-alpha agonists Bioorg. Med. Chem. Lett. 2006, 16, 1638– 1642
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Discovery and optimization of a novel series of liver X receptor-α agonists
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Bioorganic & Medicinal Chemistry Letters (2006), 16 (6), 1638-1642CODEN: BMCLE8; ISSN:0960-894X. (Elsevier B.V.)
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Abstract
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Figure 1
Figure 1. LXR modulators cocrystallized in PDB crystal structures.
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Figure 2
Figure 2. Workflow for finding novel LXR modulators.
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Figure 3
Figure 3. Binding pocket of compound 2 in 1pqc (A) and compound 5 in 1pq6 (B) with pharmacophore features of the models and highlighted cavity C1 (red), binding tunnel C2 (green), and subpocket C3 (blue); for the benefit of clear arrangement Xvols are hidden. His435, Trp443, and Phe340 are shown in ball and stick style. In part B, Phe340 changes its conformation and opens up the hydrophobic cavity C3 in order to accommodate the larger ligand compound 5.
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Figure 4
Figure 4. Pharmacophore models generated for LXR modulators. Chemical features are color-coded: hydrogen bond acceptor (HBA) red, hydrogen bond donor (HBD) green, hydrophobic (HF) yellow, aromatic ring feature (AR) blue, hydrophobic aromatic feature (HAF) blue and yellow, shape (sh), and exclusion volumes (Xvols) gray.
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Figure 5
Figure 5. Newly identified LXR agonists and their shape alignment with the query compounds. (A) 7 with query compound 2 of 1upv. (B) 8 with query compound 5 of 1pq6. (C) 9 with query compound 3 of 3fal. (D) 10 with query compound 4 of 2acl.
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Figure 6
Figure 6. ABCA1 induction by compounds 7, 8, 9, and 10 at different concentrations. The control includes ABCA1 induction of compound 2 at 1 μM (light gray) and compound 5 at 1 μM (anthracite) as well as unstimulated control with DMSO (gray) and without DMSO (black).
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Figure 7
Figure 7. Alignment of compound 7 in the LXR crystal structure (PDB code 2acl). Five hydrophobic interactions and a hydrogen bond with Ser278 (LXRβ numbering) were identified with LigandScout. His435, Trp443, and Ser278 are shown in ball and stick style.
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References
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  A review. The Liver X Receptor (LXR) α and β isoforms are members of the type II nuclear receptor family which function as a heterodimer with the Retinoid X Receptor (RXR). Upon agonist binding, the formation of the LXR/RXR heterodimer takes place and ultimately the regulation of a no. of genes begins. The LXR isoforms share 77% sequence homol., with LXRα having highest expression in liver, intestine, adipose tissue, and macrophages and LXRβ being ubiquitously expressed. The aim of this article is to review the reported-medicinal chem. strategies towards the optimization of novel non-steroidal chemotypes as LXR agonists. An anal. of the structural features important for LXR ligand binding will be given, utilizing both structural activity relation data obtained from LXR assays as well as x-ray co-crystallog. data obtained with LXR ligands and the LXR ligand binding domain (LBD). The x-ray co-crystallog. data anal. will detail the key structural interactions required for LXR binding/agonist activity and reveal the differences obsd. between chemotype classes. It has been postulated that a LXRβ selective compd. may have a beneficial outcome on the lipid profile for a ligand by dissocg. the favorable and unfavorable effects of LXR agonists. While there have been a few examples of compds. showing a modest level of LXRα selectivity, obtaining a potent LXRβ selective compd. has been more challenging. Anal. of the SAR and x-ray co-crystallog. data suggests that the rational design of a LXRβ selective compd. will not be trivial.
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11. 11
  Goodwin, B. J.; Zuercher, W. J.; Collins, J. L. Recent advances in Liver X Receptor biology and chemistry Curr. Top. Med. Chem. 2008, 8, 781– 791
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  11
  Recent advances in Liver X Receptor biology and chemistry
  Goodwin, Bryan J.; Zuercher, William J.; Collins, Jon L.
  Current Topics in Medicinal Chemistry (Sharjah, United Arab Emirates) (2008), 8 (9), 781-791CODEN: CTMCCL; ISSN:1568-0266. (Bentham Science Publishers Ltd.)
  A review. The Liver X Receptors LXRα and LXRβ are ligand-activated transcription factors that belong to the nuclear hormone receptor superfamily. Seminal studies with genetic and chem. tools were instrumental in the elucidation of cholesterol metab., gluconeogenesis, inflammation, and lipogenesis as signaling pathways that are controlled by the LXRs. First generation non-steroidal LXR agonists show beneficial effects in multiple animals models of human disease yet have not progressed in the clinic due to deleterious side effects in the liver. Numerous reports have appeared in the recent literature that disclose new LXR signaling pathways and the identification of novel LXR chemotypes that may show improved therapeutic indexes. This review will provide a brief historical perspective but will primarily focus on recent advances in LXR biol. and chem.
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12. 12
  Hu, B.; Quinet, E.; Unwalla, R.; Collini, M.; Jetter, J.; Dooley, R.; Andraka, D.; Nogle, L.; Savio, D.; Halpern, A.; Goos-Nilsson, A.; Wilhelmsson, A.; Nambi, P.; Wrobel, J. Carboxylic acid based quinolines as liver X receptor modulators that have LXR beta receptor binding selectivity Bioorg. Med. Chem. Lett. 2008, 18, 54– 59
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13. 13
  Hu, B.; Unwalla, R.; Collini, M.; Quinet, E.; Feingold, I.; Goos-Nilsson, A.; Wihelmsson, A.; Nambi, P.; Wrobel, J. Discovery and SAR of cinnolines/quinolines as liver X receptor (LXR) agonists with binding selectivity for LXR beta Biorg. Med. Chem. 2009, 17, 3519– 3527
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  13
  Discovery and SAR of cinnolines/quinolines as liver X receptor (LXR) agonists with binding selectivity for LXRβ
  Hu, Baihua; Unwalla, Raymound; Collini, Michael; Quinet, Elaine; Feingold, Irene; Goos-Nilsson, Annika; Wihelmsson, Anna; Nambi, Ponnal; Wrobel, Jay
  Bioorganic & Medicinal Chemistry (2009), 17 (10), 3519-3527CODEN: BMECEP; ISSN:0968-0896. (Elsevier B.V.)
  A series of cinnolines/quinolines was prepd. and it was found that 4-phenyl-cinnoline/quinolines with either a 2',3' or 2',5'-disubstituted benzyloxy moiety or the 1-Me-7-indole methoxy moiety on the meta position of the 4-Ph ring showed good binding selectivity for LXRβ over LXRα. The LXRβ binding selective modulators displayed good activity for inducing ABCA1 gene expression in J774 macrophage cell line and poor efficacy in the LXRα Gal4 functional assay. 26, 37 and 41 were examd. for their ability to induce SREBP-1c gene expression in Huh-7 liver cell line and they were weak partial agonists.
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14. 14
  Wrobel, J.; Steffan, R.; Bowen, S. M.; Magolda, R.; Matelan, E.; Unwalla, R.; Basso, M.; Clerin, V.; Gardell, S. J.; Nambi, P.; Quinet, E.; Reminick, J. I.; Vlasuk, G. P.; Wang, S.; Feingold, I.; Huselton, C.; Bonn, T.; Farnegardh, M.; Hansson, T.; Nilsson, A. G.; Wilhelmsson, A.; Zamaratski, E.; Evans, M. J. Indazole-based liver X receptor (LXR) modulators with maintained atherosclerotic lesion reduction activity but diminished stimulation of hepatic triglyceride synthesis J. Med. Chem. 2008, 51, 7161– 7168
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15. 15
  Fievet, C.; Staels, B. Liver X receptor modulators: Effects on lipid metabolism and potential use in the treatment of atherosclerosis Biochem. Pharmacol. 2009, 77, 1316– 1327
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  There is no corresponding record for this reference.
16. 16
  Calkin, A. C.; Tontonoz, P. Liver X receptor signaling pathways and atherosclerosis Arterioscler. Thromb. Vasc. Biol. 2010, 30, 1513– 1518
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  16
  Liver X Receptor Signaling Pathways and Atherosclerosis
  Calkin, Anna C.; Tontonoz, Peter
  Arteriosclerosis, Thrombosis, and Vascular Biology (2010), 30 (8), 1513-1518CODEN: ATVBFA; ISSN:1079-5642. (Lippincott Williams & Wilkins)
  A review. First discovered as orphan receptors, liver X receptors (LXRs) were subsequently identified as the nuclear receptor target of the cholesterol metabolites, oxysterols. There are 2 LXR receptors encoded by distinct genes: LXRα is most highly expressed in the liver, adipose, kidney, adrenal tissues, and macrophages and LXRβ is ubiquitously expressed. Despite differential tissue distribution, these isoforms have 78% homol. in their ligand-binding domain and appear to respond to the same endogenous ligands. Work over the past 10 years has shown that the LXR pathway regulates lipid metab. and inflammation via both the induction and repression of target genes. Given the importance of cholesterol regulation and inflammation in the development of cardiovascular disease, it is not surprising that activation of the LXR pathway attenuates various mechanisms underlying atherosclerotic plaque development. In this brief review, we will discuss the impact of the LXR pathway on both cholesterol metab. and atherosclerosis.
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17. 17
  Zuercher, W. J.; Buckholz, R. G.; Campobasso, N.; Collins, J. L.; Galardi, C. M.; Gampe, R. T.; Hyatt, S. M.; Merrihew, S. L.; Moore, J. T.; Oplinger, J. A.; Reid, P. R.; Spearing, P. K.; Stanley, T. B.; Stewart, E. L.; Willson, T. M. Discovery of tertiary sulfonamides as potent liver X receptor antagonists J. Med. Chem. 2010, 53, 3412– 3416
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18. 18
  Joseph, S. B.; Bradley, M. N.; Castrillo, A.; Bruhn, K. W.; Mak, P. A.; Pei, L. M.; Hogenesch, J.; O’Connell, R. M.; Cheng, G. H.; Saez, E.; Miller, J. F.; Tontonoz, P. LXR-dependent gene expression is important for macrophage survival and the innate immune response Cell 2004, 119, 299– 309
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  18
  LXR-dependent gene expression is important for macrophage survival and the innate immune response
  Joseph, Sean B.; Bradley, Michelle N.; Castrillo, Antonio; Bruhn, Kevin W.; Mak, Puiying A.; Pei, Liming; Hogenesch, John; O'Connell, Ryan M.; Cheng, Genhong; Saez, Enrique; Miller, Jeffery F.; Tontonoz, Peter
  Cell (Cambridge, MA, United States) (2004), 119 (2), 299-309CODEN: CELLB5; ISSN:0092-8674. (Cell Press)
  The liver X receptors (LXRs) are nuclear receptors with established roles in the regulation of lipid metab. We now show that LXR signaling not only regulates macrophage cholesterol metab. but also impacts antimicrobial responses. Mice lacking LXRs are highly susceptible to infection with the intracellular bacteria Listeria monocytogenes (LM). Bone marrow transplant studies point to altered macrophage function as the major determinant of susceptibility. LXR-null macrophages undergo accelerated apoptosis when challenged with LM and exhibit defective bacterial clearance in vivo. These defects result, at least in part, from loss of regulation of the antiapoptotic factor SPα, a direct target for regulation by LXRα. Expression of LXRα or SPα in macrophages inhibits apoptosis in the setting of LM infection. Our results demonstrate that LXR-dependent gene expression plays an unexpected role in innate immunity and suggest that common nuclear receptor pathways mediate macrophage responses to modified lipoproteins and intracellular pathogens.
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19. 19
  Villablanca, E. J.; Raccosta, L.; Zhou, D.; Fontana, R.; Maggioni, D.; Negro, A.; Sanvito, F.; Ponzoni, M.; Valentinis, B.; Bregni, M.; Prinetti, A.; Steffensen, K. R.; Sonnino, S.; Gustafsson, J. A.; Doglioni, C.; Bordignon, C.; Traversari, C.; Russo, V. Tumor-mediated liver X receptor-alpha activation inhibits CC chemokine receptor-7 expression on dendritic cells and dampens antitumor responses Nat. Med. 2010, 16, 98– 105
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  19
  Tumor-mediated liver X receptor-α activation inhibits CC chemokine receptor-7 expression on dendritic cells and dampens antitumor responses
  Villablanca, Eduardo J.; Raccosta, Laura; Zhou, Dan; Fontana, Raffaella; Maggioni, Daniela; Negro, Aurora; Sanvito, Francesca; Ponzoni, Maurilio; Valentinis, Barbara; Bregni, Marco; Prinetti, Alessandro; Steffensen, Knut R.; Sonnino, Sandro; Gustafsson, Jan-Ake; Doglioni, Claudio; Bordignon, Claudio; Traversari, Catia; Russo, Vincenzo
  Nature Medicine (New York, NY, United States) (2010), 16 (1), 98-105CODEN: NAMEFI; ISSN:1078-8956. (Nature Publishing Group)
  Sterol metab. has recently been linked to innate and adaptive immune responses through liver X receptor (LXR) signaling. Whether products of sterol metab. interfere with antitumor responses is currently unknown. Dendritic cells (DCs) initiate immune responses, including antitumor activity after their CC chemokine receptor-7 (CCR7)-dependent migration to lymphoid organs. Here the authors report that human and mouse tumors produce LXR ligands that inhibit CCR7 expression on maturing DCs and, therefore, their migration to lymphoid organs. In agreement with this observation, the authors detected CD83+CCR7- DCs within human tumors. Mice injected with tumors expressing the LXR ligand-inactivating enzyme sulfotransferase 2B1b (SULT2B1b) successfully controlled tumor growth by regaining DC migration to tumor-draining lymph nodes and by developing overt inflammation within tumors. The control of tumor growth was also obsd. in chimeric mice transplanted with bone marrow from mice lacking the gene encoding LXR-α (Nr1h3-/- mice). Thus, the authors show a new mechanism of tumor immunoescape involving products of cholesterol metab. The manipulation of this pathway could restore antitumor immunity in individuals with cancer.
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20. 20
  Zelcer, N.; Khanlou, N.; Clare, R.; Jiang, Q.; Reed-Geaghan, E. G.; Landreth, G. E.; Vinters, H. V.; Tontonoz, P. Attenuation of neuroinflammation and Alzheimer’s disease pathology by liver x receptors Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 10601– 10606
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21. 21
  Fitz, N. F.; Cronican, A.; Pham, T.; Fogg, A.; Fauq, A. H.; Chapman, R.; Lefterov, I.; Koldamova, R. Liver X receptor agonist treatment ameliorates amyloid pathology and memory deficits caused by high-fat diet in APP23 mice J. Neurosci. 2010, 30, 6862– 6872
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  21
  Liver X receptor agonist treatment ameliorates amyloid pathology and memory deficits caused by high-fat diet in APP23 mice
  Fitz, Nicholas F.; Cronican, Andrea; Pham, Tam; Fogg, Allison; Fauq, Abdul H.; Chapman, Robert; Lefterov, Iliya; Koldamova, Radosveta
  Journal of Neuroscience (2010), 30 (20), 6862-6872CODEN: JNRSDS; ISSN:0270-6474. (Society for Neuroscience)
  High-fat diet and certain dietary patterns are assocd. with higher incidence of sporadic Alzheimer's disease (AD) and cognitive decline. However, no specific therapy has been suggested to ameliorate the neg. effects of high fat/high cholesterol levels on cognition and amyloid pathol. Here we show that in 9-mo-old APP23 mice, a high-fat/high-cholesterol (HF) diet provided for 4 mo exacerbates the AD phenotype evaluated by behavioral, morphol., and biochem. assays. To examine the therapeutic potential of liver X receptor (LXR) ligands, APP23 mice were fed HF diet supplemented with synthetic LXR agonist T0901317 (T0). Our results demonstrate that LXR ligand treatment causes a significant redn. of memory deficits obsd. during both acquisition and retention phases of the Morris water maze. Moreover, the effects of T0 on cognition correlate with AD-like morphol. and biochem. parameters. We found a significant decrease in amyloid plaque load, insol. Aβ and sol. Aβ oligomers. In vitro expts. with primary glia demonstrate that Abca1 is essential for the proper lipidation of ApoE and mediates the effects of T0 on Aβ degrdn. by microglia. Microdialysis expts. performed on awake freely moving mice showed that T0 decreased Aβ levels in the interstitial fluid of the hippocampus, supporting the conclusion that this treatment increases Aβ clearance. The data presented conclusively shows that LXR activation in the context of a metabolic challenge has crit. effects on AD phenotype progression by attenuating Aβ deposition and facilitating its clearance.
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22. 22
  Baranowski, M. Biological role of liver X receptors J. Physiol. Pharmacol. 2008, 59, 31– 55
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  22
  Biological role of liver X receptors
  Baranowski M
  Journal of physiology and pharmacology : an official journal of the Polish Physiological Society (2008), 59 Suppl 7 (), 31-55 ISSN:.
  Liver X receptors (LXRs) are ligand-activated transcription factors of the nuclear receptor superfamily. There are two LXR isoforms termed alpha and beta which upon activation form heterodimers with retinoid X receptor and bind to LXR response element found in the promoter region of the target genes. Their endogenous agonists include a variety of oxidized cholesterol derivatives referred to as oxysterols. In the recent years LXRs have been characterized as key transcriptional regulators of lipid and carbohydrate metabolism. LXRs were shown to function as sterol sensors protecting the cells from cholesterol overload by stimulating reverse cholesterol transport and activating its conversion to bile acids in the liver. This finding led to identification of LXR agonists as potent antiatherogenic agents in rodent models of atherosclerosis. However, first-generation LXR activators were also shown to stimulate lipogenesis via sterol regulatory element binding protein-1c leading to liver steatosis and hypertriglyceridemia. Despite their lipogenic action, LXR agonists possess antidiabetic properties. LXR activation normalizes glycemia and improves insulin sensitivity in rodent models of type 2 diabetes and insulin resistance. Antidiabetic action of LXR agonists is thought to result predominantly from suppression of hepatic gluconeogenesis. However, recent studies suggest that LXR activation may also enhance peripheral glucose uptake. The purpose of this review is to summarize the present state of knowledge on the physiological and pathophysiological implications of LXRs with the special consideration of their role in lipid and carbohydrate metabolism and associated diseases.
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23. 23
  Berman, H.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.; Weissig, H.; Shindyalov, I.; Bourne, P. The Protein Data Bank Nucleic Acids Res. 2000, 28, 235– 42
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  23
  The Protein Data Bank
  Berman, Helen M.; Westbrook, John; Feng, Zukang; Gilliland, Gary; Bhat, T. N.; Weissig, Helge; Shindyalov, Ilya N.; Bourne, Philip E.
  Nucleic Acids Research (2000), 28 (1), 235-242CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)
  The Protein Data Bank (PDB; http://www.rcsb.org/pdb/)is the single worldwide archive of structural data of biol. macromols. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
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24. 24
  Berman, H.; Henrick, K.; Nakamura, H. Announcing the worldwide Protein Data Bank Nat. Struct. Mol. Biol. 2003, 10, 980– 980
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  24
  Announcing the worldwide Protein Data Bank
  Berman, Helen; Henrick, Kim; Nakamura, Haruki
  Nature Structural Biology (2003), 10 (12), 980CODEN: NSBIEW; ISSN:1072-8368. (Nature Publishing Group)
  There is no expanded citation for this reference.
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25. 25
  Farnegardh, M.; Bonn, T.; Sun, S.; Ljunggren, J.; Ahola, H.; Wilhelmsson, A.; Gustafsson, J. A.; Carlquist, M. The three-dimensional structure of the liver X receptor beta reveals a flexible ligand-binding pocket that can accommodate fundamentally different ligands J. Biol. Chem. 2003, 278, 38821– 38828
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  25
  The three-dimensional structure of the liver X receptor beta reveals a flexible ligand-binding pocket that can accommodate fundamentally different ligands
  Farnegardh Mathias; Bonn Tomas; Sun Sherry; Ljunggren Jan; Ahola Harri; Wilhelmsson Anna; Gustafsson Jan-Ake; Carlquist Mats
  The Journal of biological chemistry (2003), 278 (40), 38821-8 ISSN:0021-9258.
  The structures of the liver X receptor LXRbeta (NR1H2) have been determined in complexes with two synthetic ligands, T0901317 and GW3965, to 2.1 and 2.4 A, respectively. Together with its isoform LXRalpha (NR1H3) it regulates target genes involved in metabolism and transport of cholesterol and fatty acids. The two LXRbeta structures reveal a flexible ligand-binding pocket that can adjust to accommodate fundamentally different ligands. The ligand-binding pocket is hydrophobic but with polar or charged residues at the two ends of the cavity. T0901317 takes advantage of this by binding to His-435 close to H12 while GW3965 orients itself with its charged group in the opposite direction. Both ligands induce a fixed "agonist conformation" of helix H12 (also called the AF-2 domain), resulting in a transcriptionally active receptor.
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26. 26
  Washburn, D. G.; Hoang, T. H.; Campobasso, N.; Smallwood, A.; Parks, D. J.; Webb, C. L.; Frank, K. A.; Nord, M.; Duraiswami, C.; Evans, C.; Jaye, M.; Thompson, S. K. Synthesis and SAR of potent LXR agonists containing an indole pharmacophore Bioorg. Med. Chem. Lett. 2009, 19, 1097– 1100
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27. 27
  Chao, E. Y.; Caravella, J. A.; Watson, M. A.; Campobasso, N.; Ghisletti, S.; Billin, A. N.; Galardi, C.; Wang, P.; Laffitte, B. A.; Lannone, M. A.; Goodwin, B. J.; Nichols, J. A.; Parks, D. J.; Stewart, E.; Wiethe, R. W.; Williams, S. P.; Smallwood, A.; Pearce, K. H.; Glass, C. K.; Willson, T. M.; Zuercher, W. J.; Collins, J. L. Structure-guided design of N-phenyl tertiary amines as transrepression-selective liver X receptor modulators with anti-inflammatory activity J. Med. Chem. 2008, 51, 5758– 5765
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  27
  Structure-Guided Design of N-Phenyl Tertiary Amines as Transrepression-Selective Liver X Receptor Modulators with Anti-Inflammatory Activity
  Chao, Esther Y.; Caravella, Justin A.; Watson, Mike A.; Campobasso, Nino; Ghisletti, Serena; Billin, Andrew N.; Galardi, Cristin; Wang, Ping; Laffitte, Bryan A.; Iannone, Marie A.; Goodwin, Bryan J.; Nichols, Jason A.; Parks, Derek J.; Stewart, Eugene; Wiethe, Robert W.; Williams, Shawn P.; Smallwood, Angela; Pearce, Kenneth H.; Glass, Christopher K.; Willson, Timothy M.; Zuercher, William J.; Collins, Jon L.
  Journal of Medicinal Chemistry (2008), 51 (18), 5758-5765CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
  A cocrystal structure of T1317 (3) bound to hLXRβ was utilized in the design of a series of substituted N-Ph tertiary amines. Profiling in binding and functional assays led to the identification of LXR modulator GSK9772 (I) as a high-affinity LXRβ ligand (IC50 = 30 nM) that shows sepn. of anti-inflammatory and lipogenic activities in human macrophage and liver cell lines, resp. A cocrystal structure of the structurally related analog 19 bound to LXRβ reveals regions within the receptor that can affect receptor modulation through ligand modification. Mechanistic studies demonstrate that 20 is greater than 10-fold selective for LXR-mediated transrepression of proinflammatory gene expression vs. transactivation of lipogenic signaling pathways, thus providing an opportunity for the identification of LXR modulators with improved therapeutic indexes.
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28. 28
  Jaye, M. C.; Krawiec, J. A.; Campobasso, N.; Smallwood, A.; Qiu, C. Y.; Lu, Q.; Kerrigan, J. J.; Alvaro, M. D. L.; Laffitte, B.; Liu, W. S.; Marino, J. P.; Meyer, C. R.; Nichols, J. A.; Parks, D. J.; Perez, P.; Sarov-Blat, L.; Seepersaud, S. D.; Steplewski, K. M.; Thompson, S. K.; Wang, P.; Watson, M. A.; Webb, C. L.; Haigh, D.; Caravella, J. A.; Macphee, C. H.; Willson, T. M.; Collins, J. L. Discovery of substituted maleimides as liver X receptor agonists and determination of a ligand-bound crystal structure J. Med. Chem. 2005, 48, 5419– 5422
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  28
  Discovery of Substituted Maleimides as Liver X Receptor Agonists and Determination of a Ligand-Bound Crystal Structure
  Jaye, Michael C.; Krawiec, John A.; Campobasso, Nino; Smallwood, Angela; Qiu, Chunyan; Lu, Quinn; Kerrigan, John J.; De Los Frailes Alvaro, Maite; Laffitte, Bryan; Liu, Wu-Schyong; Marino, Joseph P., Jr.; Meyer, Craig R.; Nichols, Jason A.; Parks, Derek J.; Perez, Paloma; Sarov-Blat, Lea; Seepersaud, Sheila D.; Steplewski, Klaudia M.; Thompson, Scott K.; Wang, Ping; Watson, Mike A.; Webb, Christine L.; Haigh, David; Caravella, Justin A.; Macphee, Colin H.; Willson, Timothy M.; Collins, Jon L.
  Journal of Medicinal Chemistry (2005), 48 (17), 5419-5422CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
  Substituted 3-(phenylamino)-1H-pyrrole-2,5-diones were identified from a high throughput screen as inducers of human ATP binding cassette transporter A1 expression. Mechanism of action studies led to the identification of GSK3987 (I) as an LXR ligand. I recruits the steroid receptor coactivator-1 to human LXRα and LXRβ with EC50s of 40 nM, profiles as an LXR agonist in functional assays, and activates LXR though a mechanism that is similar to first generation LXR agonists.
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29. 29
  Kher, S.; Lake, K.; Sircar, I.; Pannala, M.; Bakir, F.; Zapf, J.; Xu, K.; Zhang, S. H.; Liu, J. P.; Morera, L.; Sakurai, N.; Jack, R.; Cheng, J. F. 2-Aryl-N-acyl indole derivatives as liver X receptor (LXR) agonists Bioorg. Med. Chem. Lett. 2007, 17, 4442– 4446
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  29
  2-Aryl-N-acyl indole derivatives as liver X receptor (LXR) agonists
  Kher, Sunil; Lake, Kirk; Sircar, Ila; Pannala, Madhavi; Bakir, Farid; Zapf, James; Xu, Kui; Zhang, Shao-Hui; Liu, Juping; Morera, Lisa; Sakurai, Naoki; Jack, Rick; Cheng, Jie-Fei
  Bioorganic & Medicinal Chemistry Letters (2007), 17 (16), 4442-4446CODEN: BMCLE8; ISSN:0960-894X. (Elsevier Ltd.)
  Structure-activity relationship studies on a series of Boc-indole derivs. as LXR agonists are described. Compd. 1 (I) was identified as an LXR agonist through structure-based virtual screening followed by high-throughput gene profiling. Replacement of the indan linker portion in 1 with an open-chain linker resulted in compds. with similar or improved in vitro potency and cellular functional activity. The Boc group at the N-1 position of the indole moiety can be replaced with a benzoyl group. The SAR studies led to the identification of compd. 8, a potent LXRβ agonist with an EC50 of 12 nM in the cofactor recruitment assay.
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30. 30
  Cheng, J. F.; Zapf, J.; Takedomi, K.; Fukushima, C.; Ogiku, T.; Zhang, S. H.; Yang, G.; Sakurai, N.; Barbosa, M.; Jack, R.; Xu, K. Combination of virtual screening and high throughput gene profiling for identification of novel liver X receptor modulators J. Med. Chem. 2008, 51, 2057– 2061
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31. 31
  Ghemtio, L.; Devignes, M. D.; Smail-Tabbone, M.; Souchet, M.; Leroux, V.; Maigret, B. Comparison of three preprocessing filters efficiency in virtual screening: Identification of new putative LXR beta regulators as a test case J. Chem. Inf. Model. 2010, 50, 701– 715
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  31
  Comparison of Three Preprocessing Filters Efficiency in Virtual Screening: Identification of New Putative LXRβ Regulators As a Test Case
  Ghemtio, Leo; Devignes, Marie-Dominique; Smail-Tabbone, Malika; Souchet, Michel; Leroux, Vincent; Maigret, Bernard
  Journal of Chemical Information and Modeling (2010), 50 (5), 701-715CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
  In silico screening methodologies are widely recognized as efficient approaches in early steps of drug discovery. However, in the virtual high-throughput screening (VHTS) context, where hit compds. are searched among millions of candidates, three-dimensional comparison techniques and knowledge discovery from databases should offer a better efficiency to finding novel drug leads than those of computationally expensive mol. dockings. Therefore, the present study aims at developing a filtering methodol. to efficiently eliminate unsuitable compds. in VHTS process. Several filters are evaluated in this paper. The first two are structure-based and rely on either geometrical docking or pharmacophore depiction. The third filter is ligand-based and uses knowledge-based and fingerprint similarity techniques. These filtering methods were tested with the Liver X Receptor (LXR) as a target of therapeutic interest, as LXR is a key regulator in maintaining cholesterol homeostasis. The results show that the three considered filters are complementary so that their combination should generate consistent compd. lists of potential hits.
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  Zhao, W.; Gu, Q.; Wang, L.; Ge, H.; Li, J.; Xu, J. Three-dimensional pharmacophore modeling of liver-X receptor agonists J. Chem. Inf. Model. 2011, 51, 2147– 2155
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  Three-Dimensional Pharmacophore Modeling of Liver-X Receptor Agonists
  Zhao, Wenxia; Gu, Qiong; Wang, Ling; Ge, Hu; Li, Jiabo; Xu, Jun
  Journal of Chemical Information and Modeling (2011), 51 (9), 2147-2155CODEN: JCISD8; ISSN:1549-9596. (American Chemical Society)
  High cholesterol levels contribute to hyperlipidemia. Liver X receptors (LXRs) are the drug targets. LXRs regulate the cholesterol absorption, biosynthesis, transportation, and metab. Novel agonists of LXR, esp. LXRβ, are attractive solns. for treating hyperlipidemia. In order to discover novel LXRβ agonists, a three-dimensional pharmacophore model was built based upon known LXRβ agonists. The model was validated with a test set, a virtual screening expt., and the FlexX docking approach. Results show that the model is capable of predicting a LXRβ agonist activity. Ligand-based virtual screening results can be refined by crosslinking by structure-based approaches. This is because two ligands that are mapped in the same way to the same pharmacophore model may have significantly different binding behaviors in the receptor's binding pocket. This paper reports our approach to identify reliable pharmacophore models through combining both ligand- and structure-based approaches.
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33. 33
  Beautrait, A.; Leroux, V.; Chavent, M.; Ghemtio, L.; Devignes, M. D.; Smaiel-Tabbone, M.; Cai, W.; Shao, X.; Moreau, G.; Bladon, P.; Yao, J.; Maigret, B. Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment J. Mol. Model. 2008, 14, 135– 148
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  Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment
  Beautrait, Alexandre; Leroux, Vincent; Chavent, Matthieu; Ghemtio, Leo; Devignes, Marie-Dominique; Smail-Tabbone, Malika; Cai, Wensheng; Shao, Xuegang; Moreau, Gilles; Bladon, Peter; Yao, Jianhua; Maigret, Bernard
  Journal of Molecular Modeling (2008), 14 (2), 135-148CODEN: JMMOFK; ISSN:0948-5023. (Springer GmbH)
  Numerous methods are available for use as part of a virtual screening strategy but, as yet, no single method is able to guarantee both a level of confidence comparable to exptl. screening and a level of computing efficiency that could drastically cut the costs of early phase drug discovery campaigns. Here, we present VSM-G (virtual screening manager for computational grids), a virtual screening platform that combines several structure-based drug design tools. VSM-G aims to be as user-friendly as possible while retaining enough flexibility to accommodate other in silico techniques as they are developed. In order to illustrate VSM-G concepts, we present a proof-of-concept study of a fast geometrical matching method based on spherical harmonics expansions surfaces. This technique is implemented in VSM-G as the first module of a multiple-step sequence tailored for high-throughput expts. We show that, using this protocol, notable enrichment of the input mol. database can be achieved against a specific target, here the liver-X nuclear receptor. The benefits, limitations and applicability of the VSM-G approach are discussed. Possible improvements of both the geometrical matching technique and its implementation within VSM-G are suggested.
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  Leach, A. R.; Gillet, V. J.; Lewis, R. A.; Taylor, R. Three-dimensional pharmacophore methods in drug discovery J. Med. Chem. 2010, 53, 539– 558
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  Three-Dimensional Pharmacophore Methods in Drug Discovery
  Leach, Andrew R.; Gillet, Valerie J.; Lewis, Richard A.; Taylor, Robin
  Journal of Medicinal Chemistry (2010), 53 (2), 539-558CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
  A review. In the first part of this Perspective the authors provide an overview of the computational 3D pharmacophore methods most commonly used in drug discovery. The authors focus in particular on the key problem of pharmacophore elucidation: the identification from a set of active mols. and their biol. activities of the key common features and their relative orientations (also called pharmacophore mapping). In the second part the authors reflect on the challenges in this field and provide some thoughts on future directions. The authors' primary goal is to provide the interested reader with a fair assessment of the current state-of-the-art in this field with an emphasis on the methods and software that in the authors' experience are most widely used in real drug discovery projects. The authors will cover both the practical aspects and some of the inherent limitations of such methods.
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  Langer, T. Pharmacophores in drug research Mol. Inform. 2010, 29, 470– 475
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  Pharmacophores in Drug Research
  Langer, Thierry
  Molecular Informatics (2010), 29 (6-7), 470-475CODEN: MIONBS; ISSN:1868-1743. (Wiley-VCH Verlag GmbH & Co. KGaA)
  A review. The pharmacophore concept in modern drug research is highlighted and the most important use examples and success stories are reviewed. These include papers from method development as well as from application areas. As indicated by the no. of publications available, the pharmacophore approach has proven to be extremely useful as interface between medicinal and computational chem., both in virtual screening and library design for efficient hit discovery, but also in the optimization of lead compds. to clin. candidates. Recent studies focus on the usage of parallel screening using pharmacophore models for bio-activity profiling and early stage risk assessment of potential side effects and toxicity due to interaction of drug candidates with anti-targets.
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  Wolber, G.; Langer, T. LigandScout: 3-D pharmacophores derived from protein-bound Ligands and their use as virtual screening filters J. Chem. Inf. Model. 2005, 45, 160– 169
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  LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters
  Wolber Gerhard; Langer Thierry
  Journal of chemical information and modeling (2005), 45 (1), 160-9 ISSN:1549-9596.
  From the historically grown archive of protein-ligand complexes in the Protein Data Bank small organic ligands are extracted and interpreted in terms of their chemical characteristics and features. Subsequently, pharmacophores representing ligand-receptor interaction are derived from each of these small molecules and its surrounding amino acids. Based on a defined set of only six types of chemical features and volume constraints, three-dimensional pharmacophore models are constructed, which are sufficiently selective to identify the described binding mode and are thus a useful tool for in-silico screening of large compound databases. The algorithms for ligand extraction and interpretation as well as the pharmacophore creation technique from the automatically interpreted data are presented and applied to a rhinovirus capsid complex as application example.
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  OEChem, version 1.7.0; OpenEye Scientific Software, I., Santa Fe, NM, USA; www.eyesopen.com, 2009.
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  Grant, J. A.; Gallardo, M. A.; Pickup, B. T. A fast method of molecular shape comparison: A simple application of a Gaussian description of molecular shape J. Comput. Chem. 1996, 17, 1653– 1666
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  A fast method of molecular shape comparison: a simple application of a Gaussian description of molecular shape
  Grant, J. A.; Gallard, M. A.; Pickup, B. T.
  Journal of Computational Chemistry (1996), 17 (14), 1653-1666CODEN: JCCHDD; ISSN:0192-8651. (Wiley)
  A gaussian description of mol. shape is used to compare the shapes of two mols. by anal. optimizing their vol. intersection. The method is applied to predict the relative orientation of ligand series binding to the proteins, thrombin, HIV protease, and thermolysin. The method is also used to quantify the degree of chirality of asym. mols. and to investigate the chirality of biphenyl and the amino acids. The shape comparison method uses the newly described shape multipoles that can also be used to describe the inherent shape of mols. Some results of calcd. shape quadrupoles are given for the ligands used in this work.
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39. 39
  Williams, S.; Bledsoe, R. K.; Collins, J. L.; Boggs, S.; Lambert, M. H.; Miller, A. B.; Moore, J.; McKee, D. D.; Moore, L.; Nichols, J.; Parks, D.; Watson, M.; Wisely, B.; Willson, T. M. X-ray crystal structure of the liver X receptor beta ligand binding domain - Regulation by a histidine-tryptophan switch J. Biol. Chem. 2003, 278, 27138– 27143
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  Ratni, H.; Blum-Kaelin, D.; Dehmlow, H.; Hartman, P.; Jablonski, P.; Masciadri, R.; Maugeais, C.; Patiny-Adam, A.; Panday, N.; Wright, M. Discovery of tetrahydro-cyclopenta[b]indole as selective LXRs modulator Bioorg. Med. Chem. Lett. 2009, 19, 1654– 1657
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  Markt, P.; Petersen, R.; Flindt, E.; Kristiansen, K.; Kirchmair, J.; Spitzer, G.; Distinto, S.; Schuster, D.; Wolber, G.; Laggner, C.; Langer, T. Discovery of novel PPAR ligands by a virtual screening approach based on pharmacophore modeling, 3D shape, and electrostatic similarity screening J. Med. Chem. 2008, 51, 6303– 17
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  Discovery of Novel PPAR Ligands by a Virtual Screening Approach Based on Pharmacophore Modeling, 3D Shape, and Electrostatic Similarity Screening
  Markt, Patrick; Petersen, Rasmus K.; Flindt, Esben N.; Kristiansen, Karsten; Kirchmair, Johannes; Spitzer, Gudrun; Distinto, Simona; Schuster, Daniela; Wolber, Gerhard; Laggner, Christian; Langer, Thierry
  Journal of Medicinal Chemistry (2008), 51 (20), 6303-6317CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
  Peroxisome proliferator-activated receptors (PPARs) are important targets for drugs used in the treatment of atherosclerosis, dyslipidemia, obesity, type 2 diabetes, and other diseases caused by abnormal regulation of the glucose and lipid metab. We applied a virtual screening workflow based on a combination of pharmacophore modeling with 3D shape and electrostatic similarity screening techniques to discover novel scaffolds for PPAR ligands. From the resulting 10 virtual screening hits, five tested pos. in human PPAR ligand-binding domain (hPPAR-LBD) transactivation assays and showed affinities for PPAR in a competitive binding assay. Compds. 5, 7, and 8 were identified as PPAR-α agonists, whereas compds. 2 and 9 showed agonistic activity for hPPAR-γ. Moreover, compd. 9 was identified as a PPAR-δ antagonist. These results demonstrate that our virtual screening protocol is able to enrich novel scaffolds for PPAR ligands that could be useful for drug development in the area of atherosclerosis, dyslipidemia, and type 2 diabetes.
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42. 42
  Noha, S. M.; Atanasov, A. G.; Schuster, D.; Markt, P.; Fakhrudin, N.; Heiss, E. H.; Schrammel, O.; Rollinger, J. M.; Stuppner, H.; Dirsch, V. M.; Wolber, G. Discovery of a novel IKK-beta inhibitor by ligand-based virtual screening techniques Bioorg. Med. Chem. Lett. 2011, 21, 577– 583
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  Fakhrudin, N.; Ladurner, A.; Atanasov, A. G.; Heiss, E. H.; Baumgartner, L.; Markt, P.; Schuster, D.; Ellmerer, E. P.; Wolber, G.; Rollinger, J. M.; Stuppner, H.; Dirsch, V. M. Computer-aided discovery, validation, and mechanistic characterization of novel neolignan activators of peroxisome proliferator-activated receptor gamma Mol. Pharmacol. 2010, 77, 559– 566
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  Waltenberger, B.; Wiechmann, K.; Bauer, J.; Markt, P.; Noha, S. M.; Wolber, G.; Rollinger, J. M.; Werz, O.; Schuster, D.; Stuppner, H. Pharmacophore modeling and virtual xcreening for novel acidic inhibitors of microsomal prostaglandin E-2 synthase-1 (mPGES-1) J. Med. Chem. 2011, 54, 3163– 3174
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  Schuster, D.; Waltenberger, B.; Kirchmair, J.; Distinto, S.; Markt, P.; Stuppner, H.; Rollinger, J. M.; Wolber, G. Predicting cyclooxygenase inhibition by three-dimensional pharmacophoric profiling. Part I: model generation, validation and applicability in ethnopharmacology Mol. Inform. 2010, 29, 75– 86
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  Predicting cyclooxygenase inhibition by three-dimensional pharmacophoric profiling. Part I: model generation, validation and applicability in ethnopharmacology
  Schuster, Daniela; Waltenberger, Birgit; Kirchmair, Johannes; Distinto, Simona; Markt, Patrick; Stuppner, Hermann; Rollinger, Judith M.; Wolber, Gerhard
  Molecular Informatics (2010), 29 (1-2), 75-86CODEN: MIONBS; ISSN:1868-1743. (Wiley-VCH Verlag GmbH & Co. KGaA)
  3D pharmacophore modeling has evolved as an established and state-of-the-art method for performing insilico predictions of biol. activity. Using one single model is limited to single binding modes, while the combination of several models bears a broader application scope. We demonstrate the generation of a complete and predictive 3D model set for cyclooxygenase 1 and 2 inhibitors, along with a selection and validation protocol optimized for parallel virtual screening. This model set was applied to explain the cyclooxygenase activity of an ethnopharmacol. known mixt. of natural products, the Thai traditional medicine "Prasaplai". Results show that rationalizing natural product activity by modern in-silico approaches is promising and can be tremendously useful in the identification of the mechanisms of action for known biol. effects of complex herbal remedies.
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  Bernotas, R. C.; Singhaus, R. R.; Kaufman, D. H.; Travins, J. M.; Ullrich, J. W.; Unwalla, R.; Quinet, E.; Evans, M.; Nambi, P.; Olland, A.; Kauppi, B.; Wilhelmsson, A.; Goos-Nilsson, A.; Wrobel, J. 4-(3-Aryloxyaryl)quinoline sulfones are potent liver X receptor agonists Bioorg. Med. Chem. Lett. 2010, 20, 209– 212
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  Spencer, T. A.; Li, D. S.; Russel, J. S.; Collins, J. L.; Bledsoe, R. K.; Consler, T. G.; Moore, L. B.; Galardi, C. M.; McKee, D. D.; Moore, J. T.; Watson, M. A.; Parks, D. J.; Lambert, M. H.; Willson, T. M. Pharmacophore analysis of the nuclear oxysterol receptor LXR alpha J. Med. Chem. 2001, 44, 886– 897
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  Yang, C. D.; McDonald, J. G.; Patel, A.; Zhang, Y.; Umetani, M.; Xu, F.; Westover, E. J.; Covey, D. F.; Mangelsdorf, D. J.; Cohen, J. C.; Hobbs, H. H. Sterol intermediates from cholesterol biosynthetic pathway as liver X receptor ligands J. Biol. Chem. 2006, 281, 27816– 27826
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  Molteni, V.; Li, X.; Nabakka, J.; Liang, F.; Wityak, J.; Koder, A.; Vargas, L.; Romeo, R.; Mitro, N.; Mak, P. A.; Seidel, M.; Haslam, J. A.; Chow, D.; Tuntland, T.; Spalding, T. A.; Brock, A.; Bradley, M.; Castrillo, A.; Tontonoz, P.; Saez, E. N-acylthiadiazolines, a new class of liver x receptor agonists with selectivity for LXR beta J. Med. Chem. 2007, 50, 4255– 4259
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  Li, L. P.; Liu, J. W.; Zhu, L. S.; Cutler, S.; Hasegawa, H.; Shan, B.; Medina, J. C. Discovery and optimization of a novel series of liver X receptor-alpha agonists Bioorg. Med. Chem. Lett. 2006, 16, 1638– 1642
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  Discovery and optimization of a novel series of liver X receptor-α agonists
  Li, Leping; Liu, Jiwen; Zhu, Liusheng; Cutler, Serena; Hasegawa, Hirohiko; Shan, Bei; Medina, Julio C.
  Bioorganic & Medicinal Chemistry Letters (2006), 16 (6), 1638-1642CODEN: BMCLE8; ISSN:0960-894X. (Elsevier B.V.)
  A novel series of hexafluorocarbinols were discovered as potent activators of the liver X receptor-α using a fluorescence polarization assay. Structure-activity relationship study led to the identification of compds. that are more potent agonists than the endogenous ligand, 24(S),25-epoxycholesterol, with similar efficacy. Several compds., including T0901317 (I), were shown to have desirable pharmacokinetic profiles suitable for in vivo studies.
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52. 52
  Liu, W. G.; Chen, S.; Dropinski, J.; Colwell, L.; Robins, M.; Szymonifka, M.; Hayes, N.; Sharma, N.; MacNaul, K.; Hernandez, M.; Burton, C.; Sparrow, C. P.; Menke, J. G.; Singh, S. B. Design, synthesis, and structure-activity relationship of podocarpic acid amides as Liver X receptor agonists for potential treatment of atherosclerosis Bioorg. Med. Chem. Lett. 2005, 15, 4574– 4578
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  Szewczyk, J. W.; Huang, S.; Chin, J.; Tian, J.; Mitnal, L.; Rosa, R. L.; Peterson, L.; Sparrow, C. P.; Adams, A. D. SAR studies: Designing potent and selective LXR agonists Bioorg. Med. Chem. Lett. 2006, 16, 3055– 3060
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  Panday, N.; Benz, J.; Blum-Kaelin, D.; Bourgeaux, V.; Dehmlow, H.; Hartman, P.; Kuhn, B.; Ratni, H.; Warot, X.; Wright, M. B. Synthesis and evaluation of anilinohexafluoroisopropanols as activators/modulators of LXR alpha and beta Bioorg. Med. Chem. Lett. 2006, 16, 5231– 5237
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  Hu, B. H.; Collini, M.; Unwalla, R.; Miller, C.; Singhaus, R.; Quinet, E.; Savio, D.; Halpern, A.; Basso, M.; Keith, J.; Clerin, V.; Chen, L.; Resmini, C.; Liu, Q. Y.; Feingold, I.; Huselton, C.; Azam, F.; Farnegardh, M.; Enroth, C.; Bonn, T.; Goos-Nilsson, A.; Wilhelmsson, A.; Nambi, P.; Wrobel, J. Discovery of phenyl acetic acid substituted quinolines as novel liver X receptor agonists for the treatment of atherosclerosis J. Med. Chem. 2006, 49, 6151– 6154
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  Discovery of Phenyl Acetic Acid Substituted Quinolines as Novel Liver X Receptor Agonists for the Treatment of Atherosclerosis
  Hu, Baihua; Collini, Michael; Unwalla, Rayomand; Miller, Christopher; Singhaus, Robert; Quinet, Elaine; Savio, Dawn; Halpern, Anita; Basso, Michael; Keith, James; Clerin, Valerie; Chen, Liang; Resmini, Christine; Liu, Qiang-Yuan; Feingold, Irene; Huselton, Christine; Azam, Farooq; Farnegardh, Mathias; Enroth, Cristofer; Bonn, Tomas; Goos-Nilsson, Annika; Wilhelmsson, Anna; Nambi, Ponnal; Wrobel, Jay
  Journal of Medicinal Chemistry (2006), 49 (21), 6151-6154CODEN: JMCMAR; ISSN:0022-2623. (American Chemical Society)
  A structure-based approach was used to optimize our new class of quinoline LXR modulators leading to Ph acetic acid substituted quinolines 15 and 16 (I). Both compds. displayed good binding affinity for LXRβ and LXRα and were potent activators in LBD transactivation assays. The compds. also increased expression of ABCA1 and stimulated cholesterol efflux in THP-1 cells. Quinoline 16 showed good oral bioavailability and in vivo efficacy in a LDLr knockout mouse model for lesions.
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  Milne, G. W. A.; Nicklaus, M. C.; Driscoll, J. S.; Wang, S. M.; Zaharevitz, D. National-Cancer-Institute drug information-system 3D Database J. Chem. Inf. Comput. Sci. 1994, 34, 1219– 1224
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  A searchable database of three-dimensional structures has been developed from the chem. database of the NCI Drug Information System (DIS), a file of about 450,000 primarily org. compds. which have been tested by NCI for anticancer activity. The DIS database is very similar in size and content to the proprietary databases used in the pharmaceutical industry; its development began in the 1950s; and this history led to a no. of problems in the generation of 3D structures.
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  Güner, O. F.; Waldman, M.; Hoffmann, R.; Kim, J. H. Strategies for Database Mining and Pharmacophore Development; International University Line: La Jolla, CA, USA, 2000.
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  Mills, J. E. J.; Dean, P. M. Three-dimensional hydrogen-bond geometry and probability information from a crystal survey J. Comput. Aided Mol. Des. 1996, 10, 607– 622
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  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.
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62. 62
  Schuster, D.; Markt, P.; Grienke, U.; Mihaly-Bison, J.; Binder, M.; Noha, S. M.; Rollinger, J. M.; Stuppner, H.; Bochkov, V. N.; Wolber, G. Pharmacophore-based discovery of FXR agonists. Part I: Model development and experimental validation Biorg. Med. Chem. 2011, 19, 7168– 7180
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  Hoerer, Stefan; Schmid, Angela; Heckel, Armin; Budzinski, Ralph-M.; Nar, Herbert
  Journal of Molecular Biology (2003), 334 (5), 853-861CODEN: JMOBAK; ISSN:0022-2836. (Elsevier)
  LXRβ belongs to the nuclear hormone receptor superfamily of ligand-activated transcription factors. Its natural ligands are supposed to be oxidized derivs. of cholesterol. Stimulation of LXRβ by agonists activates a no. of genes that are involved in the regulation of lipid metab. and cholesterol efflux from cells. Therefore, LXRβ may represent a novel therapeutic target for the treatment of dyslipidemia and atherosclerosis. Here, we report the X-ray crystal structure of the LXRβ ligand-binding domain (LBD) in complex with a synthetic agonist, T-0901317. This compd. occupies the ligand-binding pocket of the receptor, forms numerous lipophilic contacts with the protein and one crucial hydrogen bond to His435 and stabilizes the agonist conformation of the receptor ligand-binding domain. The recruitment of the AF2-region of the protein is not achieved via direct polar interactions of the ligand with protein side-chains of this helical segment, but rather via few hydrophobic contacts and probably more importantly via indirect effects involving the pre-orientation of side-chains that surround the ligand-binding pocket and form the interface to the AF2-helix. On the basis of these results we propose a binding mode and a mechanism of action for the putative natural ligands, oxidized derivs. of cholesterol.
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64. 64
  Svensson, S.; Ostberg, T.; Jacobsson, M.; Norstrom, C.; Stefansson, K.; Hallen, D.; Johansson, I. C.; Zachrisson, K.; Ogg, D.; Jendeberg, L. Crystal structure of the heterodimeric complex of LXR alpha and RXR beta ligand-binding domains in a fully agonistic conformation EMBO J. 2003, 22, 4625– 4633
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Structures and transactivation assay results of the 18 tested compounds, the comparative analysis of independent pharmacophore and shape-based screening, the test set of compounds used for validation, and the pharmacophore modeling for 3kfc. This material is available free of charge via the Internet at http://pubs.acs.org.
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Identification of Novel Liver X Receptor Activators by Structure-Based Modeling

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Abstract

Introduction

Figure 1

Results

Study Design

Figure 2

LXR Ligand Binding Pocket

Figure 3

Pharmacophore Models

Figure 4

Pharmacophore Screening

Shape Alignment

LXR Reporter Assay

Figure 5

Figure 6

Discussion

Figure 7

Conclusion

Experimental Section

Software Specification

Compound Data Sets

Pharmacophore Modeling, Screening, and Validation

Shape Alignment

LXR Reporter Assay

Supporting Information

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Author Information

Acknowledgment

Abbreviations

References

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Abstract

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

References

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Supporting Information

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