1FM9

THE 2.1 ANGSTROM RESOLUTION CRYSTAL STRUCTURE OF THE HETERODIMER OF THE HUMAN RXRALPHA AND PPARGAMMA LIGAND BINDING DOMAINS RESPECTIVELY BOUND WITH 9-CIS RETINOIC ACID AND GI262570 AND CO-ACTIVATOR PEPTIDES.



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PDB ID Mentions in PubMed Central Article count: 9

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Common angiotensin receptor blockers may directly modulate the immune system via VDR, PPAR and CCR2b.

(2006) Theor Biol Med Model 3

PubMed: 16403216 | PubMedCentral: PMC1360063 | DOI: 10.1186/1742-4682-3-1

Olmesartan Telmisartan Valsartan Irbesartan Candesartan Losartan VDR,1DB1 12, 27 0.038 14 10 35 77 VDR,1TXI 10,34 0.039 14 12 30 74 PPAR 12 0.29 12 6 61 3 CCR2b * 9* 25* 22* 9* 39* 25* AT2R1 * 0.10* 0... 10* 0.3* 0.17* 1.5* 0.50* *Note 1: CCR2b and AT2R1 are theoretical models, and may not be reliable (see text) Note 2: (conventional ligand binding data): 1,25-dihydroxyvitamin-D docks into VDR (PDB: 1DB1 ) with Ki = 0.029 nmol and into VDR (PDB: 1TXI ) with Ki= 0.059 nmol TX522 docks into VDR (PDB: 1DB1 ) with Ki = 0.071 nmol and VDR (PDB: 1TXI ) with Ki = 0.12 nmol TAK779 docks into putative CCR2b with Ki = 10 nmol GI262570 docks into PPAR (PDB: 1FM9 ) with Ki = 0.040 nmol.

ARBs exhibit an affinity for PPARgamma We extracted the coordinate data for PPARgamma from [PDB: 1FM9 ], an X-ray structure.

• 'PPAR' contains the receptor model we derived from PDB: 1FM9 together with the GI262570 ligand from PDB: 1FM9 and each of the ARBs which have low Ki values when docked with the receptor.

Publication Year: 2006

Binding-site assessment by virtual fragment screening.

(2010) PLoS One 5

PubMed: 20404926 | PubMedCentral: PMC2852417 | DOI: 10.1371/journal.pone.0010109

Drug Target PDB ID RMSD ave (Å) RMSD max (Å) Log (Hit Rate) Drug Target PDB ID RMSD ave (Å) RMSD max (Å) Log (Hit Rate) ACE 1uze 0.60 HIVRT 1vrt 1.66 1o86 0.17 0.37 0.4... 1rt1 1.51 2.45 1.75 1uzf 0.35 0.79 0.69 1c1c a 1.88 3.12 1.61 Alr2 1ah0 1.42 1rth a 1.62 2.28 1.61 1ah3 a 1.06 3.19 1.27 HMGR 1hw8 1.39 2acr a , b 0.88 1.72 1.10 1hwk 0.61 1.49 1.31 CDK2 1aq1 a 1.32 NA 1a4g 0.57 1buh a , b 1.77 3.20 1.44 1a4q a 0.48 2.11 0.52 1dm2 a 1.75 4.49 1.62 1nsc a 0.34 1.49 0.52 COX-2 1cvu 1.51 P38 MAPK 1a9u 1.00 1cx2 a 1.24 3.78 1.53 1kv1 3.84 10.41 1.16 3pgh a 1.11 3.96 1.64 1kv2 3.54 11.26 1.61 DHFR 3dfr 1.01 PDE5 1xoz 1.18 6dfr b 1.47 1.96 1.02 1xp0 0.79 2.23 1.24 ER 1l2i 1.69 PPARg 1fm6 1.46 3ert a 2.61 4.47 1.55 1fm9 a 1.47 4.64 1.62 1err a 2.01 4.39 1.61 2prg a 0.71 1.27 1.43 Fxa 1f0r 1.64 Thrombin 1ba8 1.53 1fjs 1.09 2.57 1.59 1hgt b 0.69 1.85 1.55 1ksn a 0.67 1.65 1.59 TK 1kim a 1.58 1xka a 1.27 2.46 1.56 1ki4 a 1.78 2.90 1.40 RMSD ave was defined as the sidechain RMSD based on binding site residues within a cutoff distance of 4.5 Å from crystallographic ligands; RMSD max is defined as the largest sidechain RMSD value among all the binding site residues.

Publication Year: 2010

Improved docking, screening and selectivity prediction for small molecule nuclear receptor modulators using conformational ensembles.

(2010) J Comput Aided Mol Des 24

PubMed: 20455005 | PubMedCentral: PMC2881208 | DOI: 10.1007/s10822-010-9362-4

Table 1 Composition of the nuclear receptor library Ensemble ID Description PDB IDs and co-crystallized ligand Het IDs 1 ERα− Estrogen receptor α, inactive conformation... 1xp6 (AIU), 1xqc_a (AEJ), 1sj0 (E4D), 2ouz (C3D) 2 ERα+ Estrogen receptor α, active conformation 2b1v_a (458), 2b1z_a (17M), 2fai_a (459), 1l2i_a (ETC.) 3 ERβ− Estrogen receptor β, inactive conformation 1hj1 (AOE), 1qkm (GEN), 1qkn (RAL) 4 ERβ+ Estrogen receptor β, active conformation 1u3r_a (338), 1yy4_a (4NA), 1zaf_b (789) 5 GR+ Glucocorticoid receptor, agonist—bound 1m2z_a (DEX), 1p93_a (DEX), 3bqd (DAY) 6 wtMR+ Mineralocorticoid receptor, agonist—bound 2aa7 (1CA), 2a3i (C0R), 2aa2 (AS4), 7 S810L MR+ Mineralocorticoid receptor, agonist—bound 1y9r_a (1CA), 2aa6_a (STR), 1ya3_a (STR), 2aax_a (STR) 8 PR+ Progesterone receptor, agonist—bound 1e3k _a(R18), 1zuc_b (T98), 2ovh (AS0) 9 RARγ+ Retinoic acid receptor γ, agonist—bound 1exa (394), 1fcx (184), 2lbd (REA) 10 RXRα+ Retinoic acid receptor α, agonist—bound 1fm9 (REA), 1mzn_a (BM6), 1rdt (L79), 1xvp_a (CID), 2p1u (4TN) 11 VDR+ Vitamin D3 receptor, a agonist—bound 1db1 (VDX), 1s19 (MC9), 1txi (TX5), 2har (OCC), 2has (C3O), 2hb7 (O1C) 12 wtAR+ Androgen receptor, agonist—bound 1e3g (R18), 2am9 (TES), 1t7t (DHT), 2hvc (LGD) 13 T877A AR+ Androgen receptor, agonist—bound 1gs4 (ZK5), 2ax7 (FHM), 2oz7 (CA4) 14 PPARα+ Peroxisome proliferator-activated receptor α, agonist—bound 2npa_c (MMB), 2rew (REW), 2p54 (735), 1k7l_a (544), 15 PPARδ+ Peroxisome proliferator-activated receptor δ, agonist—bound 1gwx_a (433), 1y0s_a (331), 2j14_b (GN1) 16 PPARγ+ Peroxisome proliferator-activated receptor γ, agonist—bound 1rdt (L79),1k74 (544), 1knu (YPA), 1nyx (DRF), 2f4b (EHA), 2gtk (208) 17 TRβ+ Thyroid hormone receptor β, agonist—bound 1n46_b (PFA), 1nax (IH5), 1q4x (G24), 2h6w (T3) (+): agonist-bound or active state, (−): antagonist-bound or inactive state Prediction of ligand binding geometry by single receptor cross-docking We first studied the ability of the collected pocket structures to correctly reproduce the binding geometry of their cognate ligands and other ligands in their ensembles.

Table 3 Accuracy of VLS in single receptor mode measured by their ROC AUC values Receptor PDB ID ROC % Receptor PDB ID ROC % Receptor PDB ID ROC % ERα− 1xp6 71 PR+ 1zuc_b 60 PPARα+ 2npa_c 88 1xqc_c 82 1e3k_a 75 2p54 78 1sj0 73 2ovh 88 2rew 83 2ouz 89 RARγ+ 1exa 97 1k7l_a 92 ERα+ 2b1v_a 85 1fcx 96 PPARδ+ 1y0s_a 95 2fai_a 80 2lbd 95 1gwx_a 97 1l2i_a 81 RXRα+ 2p1u 90 2j14_b 99 2b1z_a 80 1rdt 92 PPARγ+ 1rdt 89 ERβ- 1hj1 90 1mzn 88 1nyx 86 1qkn 75 1fm9 86 1k74 89 1qkm 61 1xvp 92 1knu 90 ERβ+ 1u3r_a 96 VDR+ 1db1 96 2f4b 87 1yy4_a 98 1txi 78 2gtk 91 1zaf_b 97 2has 97 TRβ+ 2h6w 93 GR+ 1m2z_a 80 1s19 76 1n46_b 93 1p93_a 75 2har 76 1q4x 93 3bdq 65 2hb7 92 1nax 91 wtMR+ 2aa7 98 wtAR+ 2hvc 81 2a3i 96 1e3g 81 2aa2 99 1t7t 87 S810LMR+ 1y9r_a 80 2am9 83 1ya3_a 95 T877AAR+ 1gs4 89 2aa6_a 91 2oz7 87 2aax_a 93 2ax7 87 The crystal structure 1rdt is a heterodimer of PPARγ and RXRα and was used separately for both receptors When used in the ensemble mode, the ligand hit lists from different structures in the ensemble were combined and each ligand was represented by its best score in the ensemble.

Publication Year: 2010

Dietary ?-eleostearic acid ameliorates experimental inflammatory bowel disease in mice by activating peroxisome proliferator-activated receptor-?.

(2011) PLoS One 6

PubMed: 21904603 | PubMedCentral: PMC3164124 | DOI: 10.1371/journal.pone.0024031

PDB Ligand ID PDB ID Reference Ligand Name 1 243 2VST [46] 13-hydroxyoctadecadienoic acid(13-HODE) 570 1FM9 [37] GI262570(Farglitazar) 4HD 2VV1 [46] (4S,5E,7Z,10Z,13Z,16Z,19Z)-4-hydroxydocosa-5,7,10,1... ,16,19-hexaenoic acid(4-HDHA) 9HO 2VSR [46] 9-hydroxyoctadecadienoic acid(9-HODE) DRH 2I4P [45] (2S)-2-[4-[2-(1,3-benzoxazol-2-yl-heptyl-amino)ethyl]phenoxy]-2-methyl-butanoic acid((2S)-ureidofibrate-like derivative) DRJ 2I4J [45] (2R)-2-[4-[2-(1,3-benzoxazol-2-yl-heptyl-amino)ethyl]phenoxy]-2-methyl-butanoic acid((2R)-ureidofibrate-like derivative) DRY 2HWQ [44] [(1-{3-[(6-benzoyl-1-propyl-2-naphthyl)oxy]propyl}-1H-indol-5-yl)oxy]acetic acid(5-substituted indoleoxyacetic acid analogue) EHA 2F4B [43] (5-{3-[(6-benzoyl-1-propyl-2-naphthyl)oxy]propoxy}-1H-indol-1-yl)acetic acid(Indol-1-yl acetic acid) ET1 3ET3 [47] 3-[5-methoxy-1-(4-methoxyphenyl)sulfonyl-indol-3-yl] propanoic acid(indeglitazar) HXA 2VV0 [46] Docosa-4,7,10,13,16,19-hexaenoic acid PTG 2ZK12ZK2 [48] 15-deoxy-delta(12,14)-prostaglandin J2 (PTG) Ligand IDs from respective PDB files were used.

Publication Year: 2011

LigMerge: a fast algorithm to generate models of novel potential ligands from sets of known binders.

(2012) Chem Biol Drug Des 80

PubMed: 22594624 | PubMedCentral: PMC3462068 | DOI: 10.1111/j.1747-0285.2012.01414.x

Receptor preparation Crystal structures of peroxisome proliferator–activated receptor (PPAR) gamma in complex with ligand 570 (PDB ID: 1FM9 ( 12 )), HIV reverse transcriptase in complex with i... hibitor 14 (PDB ID: 3C6T ( 13 )), and DHFR in complex with methotrexate [PDB ID: 3DFR ( 14 )] were used for the virtual screening studies.

Docking protocol For PPAR, AutoDock Vina ( 19 ) was used to dock both the 896 LigMerge-generated models and the 64 models of known inhibitors into the 1FM9 binding site using a box size of 40.9 Å × 44.3 Å × 46.8 Å.

Publication Year: 2012

Identification of PPARgamma partial agonists of natural origin (I): development of a virtual screening procedure and in vitro validation.

(2012) PLoS One 7

PubMed: 23226391 | PubMedCentral: PMC3511273 | DOI: 10.1371/journal.pone.0050816

The ligands farglitazar (from the PDB entry 1FM9) and nTZDpa (from the PDB entry 2Q5S) are also represented.

Full agonists Partial agonists cluster 1 cluster 2 cluster 3 cluster 4 cluster 5 1FM9 1I7I 1FM6 2GTK 2G0G 4PRG 2Q6R 2FVJ 2Q6S 1RDT 1KNU 1ZGY 3B3K 2G0H 2Q61 2WM0 1K74 2F4B 2PRG 2ATH 2Q5S 3BC5 2HWQ 2FVJ 1NYX 2Q5P 2Q8S 2HWR 1ZEO 2HFP 2P4Y Generation of Structure-Based Pharmacophores LigandScout v2.03 (Inte:ligand, Vienna, Austria, http://www.inteligand.com/ligandscout/ ) [33] , [34] was used for the analysis of the 31 PPARγ structures from Table 5 and the analysis of the possible interactions between the crystallized ligands and the ligand-binding pocket of PPARγ.

g001 Figure 1 Binding models of (A) the PPARγ full agonist Farglitazar (crystal structure 1FM9) and (B) the PPARγ partial agonist nTZDpa (crystal structure 2Q5S).

Publication Year: 2012

Identification of PPARgamma partial agonists of natural origin (II): in silico prediction in natural extracts with known antidiabetic activity.

(2013) PLoS One 8

PubMed: 23405231 | PubMedCentral: PMC3566095 | DOI: 10.1371/journal.pone.0055889

This pharmacophore is formed by 5 sites (two hydrogen-bond acceptors and three hydrophobic sites) that are present in most of the validated 19 complexes of full agonists (where validated means that th... coordinates for the ligand and the PPARγ active site are reliable according to their corresponding electron density map) and is completed with receptor-based excluded volumes obtained from the PDB file coded as 1FM9.

Publication Year: 2013

Improving structural similarity based virtual screening using background knowledge.

(2013) J Cheminform 5

PubMed: 24341870 | PubMedCentral: PMC3928642 | DOI: 10.1186/1758-2946-5-50

Table 2 Overview of the used DuD data sets Protein PDB code Ligands Decoys Protein class minsup fp_length HMGR [PDB:1HW8] 35 1242 other enzyme 0.9 66 ER [PDB:3ERT] 39 1399 nuclear hormone receptor 0.7... 62 PPAR γ [PDB:1FM9] 81 2910 nuclear hormone receptor 0.96 90 P38 MAP [PDB:1KV2] 234 8399 kinase 0.83 57 TK [PDB:1KIM] 22 785 kinase 0.9 74 FXa [PDB:1F0R] 142 5102 serine protease 0.8 81 ADA [PDB:1STW] 23 822 metalloenzyme 0.8 70 DHFR [PDB:3DFR] 201 7150 folate enzyme 0.8 70 AChE [PDB:1EVE] 105 3732 other enzyme 0.77 93 COX-2 [PDB:1CX2] 349 12491 other enzyme 0.6 65 Overview of the used DuD data sets.

Publication Year: 2013

Structure-based druggability assessment of the mammalian structural proteome with inclusion of light protein flexibility.

(2014) PLoS Comput Biol 10

PubMed: 25079060 | PubMedCentral: PMC4117425 | DOI: 10.1371/journal.pcbi.1003741

Target Structural data Docking-based druggability Protein flexibility Variation PDB ID RMSD ave (Å) [A] dock hit rate [B] DScore+ [A] [B] CDK2 1aq1 1.32 1.7 21% 11% 1buh 1.8 1.44 1.7 1dm2 1.8 ... .62 1.9 ER 1l2i 1.69 2.9 9% 7% 3ert 2.6 1.55 2.7 1err 2.0 1.61 2.8 HIV RT 1vrt 1.66 2.5 8% 13% 1rt1 1.5 1.75 2.3 1c1c 1.9 1.61 2.2 1rth 1.6 1.61 2.3 p38α 1a9u 1.00 1.8 49% 15% kinase 1kv1 3.8 1.16 2.1 1kv2 3.5 1.61 2.1 PPARγ 1fm6 1.46 2.9 13% 34% 1fm9 1.5 1.62 3.0 2prg 0.7 1.43 2.1 TK 1kim 1.58 2.7 12% 4% 1ki4 1.8 1.40 2.6 IL-2 1z92 0.13 * 107% 13% 1py2 2.6 0.62 * 1m48 2.5 0.62 * Bcl-XL 2bzw 1.04 2.4 21% 4% 2yxj 2.5 0.84 2.5 TNF 1tnf 0.95 2.4 1% 18% 2az5 2.9 0.96 2.0 MDM2 1ycr 0.45 2.5 69% 18% 1rv1 1.8 0.92 2.2 1t4e 1.6 0.66 2.1 HPV E2 1tue -0.24 * 323% 31% 1r6n 2.8 1.02 * Targets are from Huang and Jacobson [17] , and include all targets where at least two structures have an RMSD ave greater than 1.5 Å.

Publication Year: 2014