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Discovery of Novel Agonists and Antagonists of the Free Fatty Acid Receptor 1 (FFAR1) Using Virtual Screening

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Laboratory of Biological Modeling, and Clinical Endocrinology Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892
* Corresponding authors. (S.C.) E-mail: [email protected]. Phone: 301-451-7353 . Fax: 301-443-8000. (M.C.G.) E-mail: [email protected]. Phone: 301-496-4128 . Fax: 301-496-9943.
†Laboratory of Biological Modeling.
‡Clinical Endocrinology Branch.
§These authors have contributed equally to this work.
Cite this: J. Med. Chem. 2008, 51, 3, 625–633
Publication Date (Web):January 15, 2008
https://doi.org/10.1021/jm7012425
Copyright © This article not subject to U.S. Copyright. Published 2008 by the American Chemical Society

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    Abstract

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    The G-protein-coupled receptor free fatty acid receptor 1 (FFAR1), previously named GPR40, is a possible novel target for the treatment of type 2 diabetes. In an attempt to identify new ligands for this receptor, we performed virtual screening (VS) based on two-dimensional (2D) similarity, three-dimensional (3D) pharmacophore searches, and docking studies by using the structure of known agonists and our model of the ligand binding site, which was validated by mutagenesis. VS of a database of 2.6 million compounds followed by extraction of structural neighbors of functionally confirmed hits resulted in identification of 15 compounds active at FFAR1 either as full agonists, partial agonists, or pure antagonists. Site-directed mutagenesis and docking studies revealed different patterns of ligand–receptor interactions and provided important information on the role of specific amino acids in binding and activation of FFAR1.

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    Table enlisting the 52 compounds selected by virtual screening and experimentally tested. Docking poses of selected compounds at FFAR1. This material is available free of charge via the Internet at http://pubs.acs.org.

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    2. Dong-Oh Yoon, Xiaodi Zhao, Dohyun Son, Jung Tae Han, Jaesook Yun, Dongyun Shin, and Hyun-Ju Park . SAR Studies of Indole-5-propanoic Acid Derivatives To Develop Novel GPR40 Agonists. ACS Medicinal Chemistry Letters 2017, 8 (12) , 1336-1340. https://doi.org/10.1021/acsmedchemlett.7b00460
    3. Graeme Milligan, Bharat Shimpukade, Trond Ulven, and Brian D. Hudson . Complex Pharmacology of Free Fatty Acid Receptors. Chemical Reviews 2017, 117 (1) , 67-110. https://doi.org/10.1021/acs.chemrev.6b00056
    4. Teague Sterling and John J. Irwin . ZINC 15 – Ligand Discovery for Everyone. Journal of Chemical Information and Modeling 2015, 55 (11) , 2324-2337. https://doi.org/10.1021/acs.jcim.5b00559
    5. Albert J. Kooistra, Rob Leurs, Iwan J. P. de Esch, and Chris de Graaf . Structure-Based Prediction of G-Protein-Coupled Receptor Ligand Function: A β-Adrenoceptor Case Study. Journal of Chemical Information and Modeling 2015, 55 (5) , 1045-1061. https://doi.org/10.1021/acs.jcim.5b00066
    6. Bahareh Honarparvar, Thavendran Govender, Glenn E. M. Maguire, Mahmoud E. S. Soliman, and Hendrik G. Kruger . Integrated Approach to Structure-Based Enzymatic Drug Design: Molecular Modeling, Spectroscopy, and Experimental Bioactivity. Chemical Reviews 2014, 114 (1) , 493-537. https://doi.org/10.1021/cr300314q
    7. G. Madhavi Sastry, V. S. Sandeep Inakollu, and Woody Sherman . Boosting Virtual Screening Enrichments with Data Fusion: Coalescing Hits from Two-Dimensional Fingerprints, Shape, and Docking. Journal of Chemical Information and Modeling 2013, 53 (7) , 1531-1542. https://doi.org/10.1021/ci300463g
    8. Yasushi Yoshikawa, Shinya Oishi, Tatsuhiko Kubo, Noriko Tanahara, Nobutaka Fujii, and Toshio Furuya . Optimized Method of G-Protein-Coupled Receptor Homology Modeling: Its Application to the Discovery of Novel CXCR7 Ligands. Journal of Medicinal Chemistry 2013, 56 (11) , 4236-4251. https://doi.org/10.1021/jm400307y
    9. Elisabeth Christiansen, Maria E. Due-Hansen, Christian Urban, Manuel Grundmann, Johannes Schmidt, Steffen V. F. Hansen, Brian D. Hudson, Mohamed Zaibi, Stine B. Markussen, Ellen Hagesaether, Graeme Milligan, Michael A. Cawthorne, Evi Kostenis, Matthias U. Kassack, and Trond Ulven . Discovery of a Potent and Selective Free Fatty Acid Receptor 1 Agonist with Low Lipophilicity and High Oral Bioavailability. Journal of Medicinal Chemistry 2013, 56 (3) , 982-992. https://doi.org/10.1021/jm301470a
    10. Hong Kang, Zhen Sheng, Ruixin Zhu, Qi Huang, Qi Liu, and Zhiwei Cao . Virtual Drug Screen Schema Based on Multiview Similarity Integration and Ranking Aggregation. Journal of Chemical Information and Modeling 2012, 52 (3) , 834-843. https://doi.org/10.1021/ci200481c
    11. Francesca Fanelli and Pier G. De Benedetti . Update 1 of: Computational Modeling Approaches to Structure–Function Analysis of G Protein-Coupled Receptors. Chemical Reviews 2011, 111 (12) , PR438-PR535. https://doi.org/10.1021/cr100437t
    12. Chris de Graaf, Albert J. Kooistra, Henry F. Vischer, Vsevolod Katritch, Martien Kuijer, Mitsunori Shiroishi, So Iwata, Tatsuro Shimamura, Raymond C. Stevens, Iwan J. P. de Esch, and Rob Leurs . Crystal Structure-Based Virtual Screening for Fragment-like Ligands of the Human Histamine H1 Receptor. Journal of Medicinal Chemistry 2011, 54 (23) , 8195-8206. https://doi.org/10.1021/jm2011589
    13. Elisabeth Christiansen, Christian Urban, Manuel Grundmann, Maria E. Due-Hansen, Ellen Hagesaether, Johannes Schmidt, Leonardo Pardo, Susanne Ullrich, Evi Kostenis, Matthias Kassack, and Trond Ulven . Identification of a Potent and Selective Free Fatty Acid Receptor 1 (FFA1/GPR40) Agonist with Favorable Physicochemical and in Vitro ADME Properties. Journal of Medicinal Chemistry 2011, 54 (19) , 6691-6703. https://doi.org/10.1021/jm2005699
    14. Elisabeth Christiansen, Maria E. Due-Hansen, Christian Urban, Nicole Merten, Michael Pfleiderer, Kasper K. Karlsen, Sanne S. Rasmussen, Mette Steensgaard, Alexandra Hamacher, Johannes Schmidt, Christel Drewke, Rasmus Koefoed Petersen, Karsten Kristiansen, Susanne Ullrich, Evi Kostenis, Matthias U. Kassack, and Trond Ulven . Structure−Activity Study of Dihydrocinnamic Acids and Discovery of the Potent FFA1 (GPR40) Agonist TUG-469. ACS Medicinal Chemistry Letters 2010, 1 (7) , 345-349. https://doi.org/10.1021/ml100106c
    15. Thomas Klabunde, Clemens Giegerich and Andreas Evers. Sequence-Derived Three-Dimensional Pharmacophore Models for G-Protein-Coupled Receptors and Their Application in Virtual Screening. Journal of Medicinal Chemistry 2009, 52 (9) , 2923-2932. https://doi.org/10.1021/jm9001346
    16. Lu Tan, Eugen Lounkine and Jürgen Bajorath. Similarity Searching Using Fingerprints of Molecular Fragments Involved in Protein−Ligand Interactions. Journal of Chemical Information and Modeling 2008, 48 (12) , 2308-2312. https://doi.org/10.1021/ci800322y
    17. Takayoshi Suzuki, Sou-ichi Igari, Akira Hirasawa, Mie Hata, Masaji Ishiguro, Hiroki Fujieda, Yukihiro Itoh, Tatsuya Hirano, Hidehiko Nakagawa, Michitaka Ogura, Makoto Makishima, Gozoh Tsujimoto and Naoki Miyata. Identification of G protein-coupled receptor 120-selective agonists derived from PPARγ agonists. Journal of Medicinal Chemistry 2008, 51 (23) , 7640-7644. https://doi.org/10.1021/jm800970b
    18. Elisabeth Christiansen, Christian Urban, Nicole Merten, Kathrin Liebscher, Kasper K. Karlsen, Alexandra Hamacher, Andreas Spinrath, Andrew D. Bond, Christel Drewke, Susanne Ullrich, Matthias U. Kassack, Evi Kostenis and Trond Ulven. Discovery of Potent and Selective Agonists for the Free Fatty Acid Receptor 1 (FFA1/GPR40), a Potential Target for the Treatment of Type II Diabetes. Journal of Medicinal Chemistry 2008, 51 (22) , 7061-7064. https://doi.org/10.1021/jm8010178
    19. Chris de Graaf and Didier Rognan. Selective Structure-Based Virtual Screening for Full and Partial Agonists of the β2 Adrenergic Receptor. Journal of Medicinal Chemistry 2008, 51 (16) , 4978-4985. https://doi.org/10.1021/jm800710x
    20. Dapinder Pal Singh Loona, Bhanuranjan Das, Ramandeep Kaur, Rajnish Kumar, Ashok Kumar Yadav. Free Fatty Acid Receptors (FFARs): Emerging Therapeutic Targets for the Management of Diabetes Mellitus. Current Medicinal Chemistry 2023, 30 (30) , 3404-3440. https://doi.org/10.2174/0929867329666220927113614
    21. Yuta Yamamoto, Katsuya Narumi, Naoko Yamagishi, Toshio Nishi, Takao Ito, Ken Iseki, Masaki Kobayashi, Yoshimitsu Kanai. Oral administration of linoleic acid immediately before glucose load ameliorates postprandial hyperglycemia. Frontiers in Pharmacology 2023, 14 https://doi.org/10.3389/fphar.2023.1197743
    22. Chia-Ju Hsieh, Sam Giannakoulias, E. James Petersson, Robert H. Mach. Computational Chemistry for the Identification of Lead Compounds for Radiotracer Development. Pharmaceuticals 2023, 16 (2) , 317. https://doi.org/10.3390/ph16020317
    23. Ashwani K. Dhingra, Bhawna Chopra, Sakshi Bhardwaj, Ajmer Singh Grewal, Kumar Guarve. Virtual screening. 2023, 223-236. https://doi.org/10.1016/B978-0-323-99137-7.00007-1
    24. Brian J. Bender, Stefan Gahbauer, Andreas Luttens, Jiankun Lyu, Chase M. Webb, Reed M. Stein, Elissa A. Fink, Trent E. Balius, Jens Carlsson, John J. Irwin, Brian K. Shoichet. A practical guide to large-scale docking. Nature Protocols 2021, 16 (10) , 4799-4832. https://doi.org/10.1038/s41596-021-00597-z
    25. Lata Rani, Ajmer Singh Grewal, Neelam Sharma, Sukhbir Singh. Recent Updates on Free Fatty Acid Receptor 1 (GPR-40) Agonists for the Treatment of Type 2 Diabetes Mellitus. Mini-Reviews in Medicinal Chemistry 2021, 21 (4) , 426-470. https://doi.org/10.2174/1389557520666201023141326
    26. Neetu Jabalia, Atul Kumar, Vinit Kumar, Reshma Rani. In Silico Approach in Drug Design and Drug Discovery: An Update. 2021, 245-271. https://doi.org/10.1007/978-981-15-8936-2_10
    27. Estela Lorza-Gil, Gabriele Kaiser, Elisabeth Rexen Ulven, Gabriele M. König, Felicia Gerst, Morgana Barroso Oquendo, Andreas L. Birkenfeld, Hans-Ulrich Häring, Evi Kostenis, Trond Ulven, Susanne Ullrich. FFA2-, but not FFA3-agonists inhibit GSIS of human pseudoislets: a comparative study with mouse islets and rat INS-1E cells. Scientific Reports 2020, 10 (1) https://doi.org/10.1038/s41598-020-73467-5
    28. Yuhang Gong, Jingjing Chen, Yongzeng Jin, Chen Wang, Menglin Zheng, Ling He. GW9508 ameliorates cognitive impairment via the cAMP-CREB and JNK pathways in APPswe/PS1dE9 mouse model of Alzheimer's disease. Neuropharmacology 2020, 164 , 107899. https://doi.org/10.1016/j.neuropharm.2019.107899
    29. Neha M. Chitre, Nader H. Moniri, Kevin S. Murnane. Omega-3 Fatty Acids as Druggable Therapeutics for Neurodegenerative Disorders. CNS & Neurological Disorders - Drug Targets 2020, 18 (10) , 735-749. https://doi.org/10.2174/1871527318666191114093749
    30. Jinan Wang, Apurba Bhattarai, Waseem Imtiaz Ahmad, Treyton S. Farnan, Karen Priyadarshini John, Yinglong Miao. Computer-aided GPCR drug discovery. 2020, 283-293. https://doi.org/10.1016/B978-0-12-816228-6.00015-5
    31. Ning Kang, Xiao‐Lei Wang, Yaxue Zhao. Discovery of small molecule agonists targeting neuropeptide Y4 receptor using homology modeling and virtual screening. Chemical Biology & Drug Design 2019, 94 (6) , 2064-2072. https://doi.org/10.1111/cbdd.13611
    32. Eliane Briand, Ragnar Thomsen, Kristian Linnet, Henrik Berg Rasmussen, Søren Brunak, Olivier Taboureau. Combined Ensemble Docking and Machine Learning in Identification of Therapeutic Agents with Potential Inhibitory Effect on Human CES1. Molecules 2019, 24 (15) , 2747. https://doi.org/10.3390/molecules24152747
    33. Yu Li, Xue Yang, Hui Zhang, Qiuhong Wu. Pharmacokinetics and metabolism of GW9508 in rat by liquid chromatography/electrospray ionization tandem mass spectrometry. Journal of Pharmaceutical and Biomedical Analysis 2019, 170 , 176-186. https://doi.org/10.1016/j.jpba.2019.03.040
    34. K. Rohini, V. Shanthi. Hyphenated 3D-QSAR statistical model-drug repurposing analysis for the identification of potent neuraminidase inhibitor. Cell Biochemistry and Biophysics 2018, 76 (3) , 357-376. https://doi.org/10.1007/s12013-018-0844-7
    35. Xiaojing Yuan, Yechun Xu. Recent Trends and Applications of Molecular Modeling in GPCR–Ligand Recognition and Structure-Based Drug Design. International Journal of Molecular Sciences 2018, 19 (7) , 2105. https://doi.org/10.3390/ijms19072105
    36. Khaled M. Darwish, Ismail Salama, Samia Mostafa, Mohamed S. Gomaa, El-Sayed Khafagy, Mohamed A. Helal. Synthesis, biological evaluation, and molecular docking investigation of benzhydrol- and indole-based dual PPAR-γ/FFAR1 agonists. Bioorganic & Medicinal Chemistry Letters 2018, 28 (9) , 1595-1602. https://doi.org/10.1016/j.bmcl.2018.03.051
    37. Rohini K, Shanthi V. Discovery of Potent Neuraminidase Inhibitors Using a Combination of Pharmacophore-Based Virtual Screening and Molecular Simulation Approach. Applied Biochemistry and Biotechnology 2018, 184 (4) , 1421-1440. https://doi.org/10.1007/s12010-017-2625-y
    38. Zheng Li, Xue Xu, Wenlong Huang, Hai Qian. Free Fatty Acid Receptor 1 (FFAR1) as an Emerging Therapeutic Target for Type 2 Diabetes Mellitus: Recent Progress and Prevailing Challenges. Medicinal Research Reviews 2018, 38 (2) , 381-425. https://doi.org/10.1002/med.21441
    39. Wei Zhang, Wenyan Lu, Subramaniam Ananthan, Mark J. Suto, Yonghe Li. Discovery of novel frizzled-7 inhibitors by targeting the receptor’s transmembrane domain. Oncotarget 2017, 8 (53) , 91459-91470. https://doi.org/10.18632/oncotarget.20665
    40. Mathias M. von Behren, Matthias Rarey. Ligand-based virtual screening under partial shape constraints. Journal of Computer-Aided Molecular Design 2017, 31 (4) , 335-347. https://doi.org/10.1007/s10822-017-0011-z
    41. Jianyong Yang, Zheng Li, Huilan Li, Chunxia Liu, Nasi Wang, Wei Shi, Chen Liao, Xingguang Cai, Wenlong Huang, Hai Qian. Design, synthesis and structure–activity relationship studies of novel free fatty acid receptor 1 agonists bearing amide linker. Bioorganic & Medicinal Chemistry 2017, 25 (8) , 2445-2450. https://doi.org/10.1016/j.bmc.2017.03.001
    42. M. Congreve, A. Bortolato, G. Brown, R.M. Cooke. Modeling and Design for Membrane Protein Targets. 2017, 145-188. https://doi.org/10.1016/B978-0-12-409547-2.12358-3
    43. Arnau Cordomí, Daniel Fourmy, Irina G Tikhonova. Gut hormone GPCRs: structure, function, drug discovery. Current Opinion in Pharmacology 2016, 31 , 63-67. https://doi.org/10.1016/j.coph.2016.09.001
    44. Tony Ngo, Irina Kufareva, James LJ Coleman, Robert M Graham, Ruben Abagyan, Nicola J Smith. Identifying ligands at orphan GPCRs: current status using structure‐based approaches. British Journal of Pharmacology 2016, 173 (20) , 2934-2951. https://doi.org/10.1111/bph.13452
    45. Albert J. Kooistra, Henry F. Vischer, Daniel McNaught-Flores, Rob Leurs, Iwan J. P. de Esch, Chris de Graaf. Function-specific virtual screening for GPCR ligands using a combined scoring method. Scientific Reports 2016, 6 (1) https://doi.org/10.1038/srep28288
    46. Khaled M. Darwish, Ismail Salama, Samia Mostafa, Mohamed S. Gomaa, Mohamed A. Helal. Design, synthesis, and biological evaluation of novel thiazolidinediones as PPARγ/FFAR1 dual agonists. European Journal of Medicinal Chemistry 2016, 109 , 157-172. https://doi.org/10.1016/j.ejmech.2015.12.049
    47. Takafumi Hara. Ligands at Free Fatty Acid Receptor 1 (GPR40). 2016, 1-16. https://doi.org/10.1007/164_2016_59
    48. Steffen V. F. Hansen, Trond Ulven. Pharmacological Tool Compounds for the Free Fatty Acid Receptor 4 (FFA4/GPR120). 2016, 33-56. https://doi.org/10.1007/164_2016_60
    49. Durba Sengupta, Manali Joshi, Chaitanya A. Athale, Amitabha Chattopadhyay. What can simulations tell us about GPCRs. 2016, 429-452. https://doi.org/10.1016/bs.mcb.2015.11.007
    50. Irina G. Tikhonova, Elena Poerio. Free fatty acid receptors: structural models and elucidation of ligand binding interactions. BMC Structural Biology 2015, 15 (1) https://doi.org/10.1186/s12900-015-0044-2
    51. Zheng Li, Xuekun Wang, Xue Xu, Jianyong Yang, Qianqian Qiu, Hao Qiang, Wenlong Huang, Hai Qian. Design, synthesis and structure–activity relationship studies of novel phenoxyacetamide-based free fatty acid receptor 1 agonists for the treatment of type 2 diabetes. Bioorganic & Medicinal Chemistry 2015, 23 (20) , 6666-6672. https://doi.org/10.1016/j.bmc.2015.09.010
    52. G Milligan, E Alvarez‐Curto, K R Watterson, T Ulven, B D Hudson. Characterizing pharmacological ligands to study the long‐chain fatty acid receptors GPR 40/ FFA 1 and GPR 120/ FFA 4. British Journal of Pharmacology 2015, 172 (13) , 3254-3265. https://doi.org/10.1111/bph.12879
    53. Ashutosh Kumar, Kam Y.J. Zhang. Hierarchical virtual screening approaches in small molecule drug discovery. Methods 2015, 71 , 26-37. https://doi.org/10.1016/j.ymeth.2014.07.007
    54. Claudio N. Cavasotto, Damián Palomba. Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models. Chemical Communications 2015, 51 (71) , 13576-13594. https://doi.org/10.1039/C5CC05050B
    55. Kenneth A. Jacobson, Stefano Costanzi, Silvia Paoletta. Computational studies to predict or explain G protein coupled receptor polypharmacology. Trends in Pharmacological Sciences 2014, 35 (12) , 658-663. https://doi.org/10.1016/j.tips.2014.10.009
    56. Mohamed A. Helal, Khaled M. Darwish, Mohamed A. Hammad. Homology modeling and explicit membrane molecular dynamics simulation to delineate the mode of binding of thiazolidinediones into FFAR1 and the mechanism of receptor activation. Bioorganic & Medicinal Chemistry Letters 2014, 24 (22) , 5330-5336. https://doi.org/10.1016/j.bmcl.2014.07.043
    57. Arumugam Ramachandran Muralidharan, Chandrabose Selvaraj, Sanjeev Kumar Singh, C. A. Nelson Jesudasan, Pitchairaj Geraldine, Philip A. Thomas. Virtual screening based on pharmacophoric features of known calpain inhibitors to identify potent inhibitors of calpain. Medicinal Chemistry Research 2014, 23 (5) , 2445-2455. https://doi.org/10.1007/s00044-013-0842-7
    58. Sihui Yao, Tao Lu, Zifan Zhou, Haichun Liu, Haoliang Yuan, Ting Ran, Shuai Lu, Yanmin Zhang, Zhipeng Ke, Jinxing Xu, Xiao Xiong, Yadong Chen. An efficient multistep ligand-based virtual screening approach for GPR40 agonists. Molecular Diversity 2014, 18 (1) , 183-193. https://doi.org/10.1007/s11030-013-9493-3
    59. Stefan Offermanns. Free Fatty Acid (FFA) and Hydroxy Carboxylic Acid (HCA) Receptors. Annual Review of Pharmacology and Toxicology 2014, 54 (1) , 407-434. https://doi.org/10.1146/annurev-pharmtox-011613-135945
    60. Y.C. Martin. Applications of Pharmacophore Mapping☆. 2014https://doi.org/10.1016/B978-0-12-409547-2.11305-8
    61. Albert J. Kooistra, Rob Leurs, Iwan J. P. de Esch, Chris de Graaf. From Three-Dimensional GPCR Structure to Rational Ligand Discovery. 2014, 129-157. https://doi.org/10.1007/978-94-007-7423-0_7
    62. Ryan G. Coleman, Michael Carchia, Teague Sterling, John J. Irwin, Brian K. Shoichet, . Ligand Pose and Orientational Sampling in Molecular Docking. PLoS ONE 2013, 8 (10) , e75992. https://doi.org/10.1371/journal.pone.0075992
    63. Mahmoud E. S. Soliman. A Hybrid Structure/Pharmacophore-Based Virtual Screening Approach to Design Potential Leads: A Computer-Aided Design of South African HIV-1 Subtype C Protease Inhibitors. Drug Development Research 2013, 74 (5) , 283-295. https://doi.org/10.1002/ddr.21078
    64. Fengxiao Wang, Yadong Chen. Pharmacophore models generation by catalyst and phase consensus-based virtual screening protocol against PI3Kα inhibitors. Molecular Simulation 2013, 39 (7) , 529-544. https://doi.org/10.1080/08927022.2012.751592
    65. Stefano Costanzi. Modeling G protein-coupled receptors and their interactions with ligands. Current Opinion in Structural Biology 2013, 23 (2) , 185-190. https://doi.org/10.1016/j.sbi.2013.01.008
    66. Santiago Vilar, Stefano Costanzi. Application of Monte Carlo-Based Receptor Ensemble Docking to Virtual Screening for GPCR Ligands. 2013, 263-278. https://doi.org/10.1016/B978-0-12-407865-9.00014-5
    67. Albert J. Kooistra, Luc Roumen, Rob Leurs, Iwan J.P. de Esch, Chris de Graaf. From Heptahelical Bundle to Hits from the Haystack. 2013, 279-336. https://doi.org/10.1016/B978-0-12-407865-9.00015-7
    68. L. Roumen, D.J. Scholten, P. de Kruijf, I.J.P. de Esch, R. Leurs, C. de Graaf. C(X)CR in silico: Computer-aided prediction of chemokine receptor–ligand interactions. Drug Discovery Today: Technologies 2012, 9 (4) , e281-e291. https://doi.org/10.1016/j.ddtec.2012.05.002
    69. Brian D. Hudson, Elisabeth Christiansen, Irina G. Tikhonova, Manuel Grundmann, Evi Kostenis, David R. Adams, Trond Ulven, Graeme Milligan. Chemically engineering ligand selectivity at the free fatty acid receptor 2 based on pharmacological variation between species orthologs. The FASEB Journal 2012, 26 (12) , 4951-4965. https://doi.org/10.1096/fj.12-213314
    70. Kenneth A. Jacobson, Stefano Costanzi. New Insights for Drug Design from the X-Ray Crystallographic Structures of G-Protein-Coupled Receptors. Molecular Pharmacology 2012, 82 (3) , 361-371. https://doi.org/10.1124/mol.112.079335
    71. Clara C. Blad, Cong Tang, Stefan Offermanns. G protein-coupled receptors for energy metabolites as new therapeutic targets. Nature Reviews Drug Discovery 2012, 11 (8) , 603-619. https://doi.org/10.1038/nrd3777
    72. Wenting Tai, Tao Lu, Haoliang Yuan, Fengxiao Wang, Haichun Liu, Shuai Lu, Ying Leng, Weiwei Zhang, Yulei Jiang, Yadong Chen. Pharmacophore modeling and virtual screening studies to identify new c-Met inhibitors. Journal of Molecular Modeling 2012, 18 (7) , 3087-3100. https://doi.org/10.1007/s00894-011-1328-5
    73. Michael M. Mysinger, Dahlia R. Weiss, Joshua J. Ziarek, Stéphanie Gravel, Allison K. Doak, Joel Karpiak, Nikolaus Heveker, Brian K. Shoichet, Brian F. Volkman. Structure-based ligand discovery for the protein–protein interface of chemokine receptor CXCR4. Proceedings of the National Academy of Sciences 2012, 109 (14) , 5517-5522. https://doi.org/10.1073/pnas.1120431109
    74. Christofer S. Tautermann. Target Based Virtual Screening by Docking into Automatically Generated GPCR Models. 2012, 255-270. https://doi.org/10.1007/978-1-62703-023-6_15
    75. Santiago Vilar, Stefano Costanzi. Predicting the Biological Activities Through QSAR Analysis and Docking-Based Scoring. 2012, 271-284. https://doi.org/10.1007/978-1-62703-023-6_16
    76. Chris de Graaf, Chantal Rein, David Piwnica, Fabrizio Giordanetto, Didier Rognan. Structure-Based Discovery of Allosteric Modulators of Two Related Class B G-Protein-Coupled Receptors. ChemMedChem 2011, 6 (12) , 2159-2169. https://doi.org/10.1002/cmdc.201100317
    77. Jens Carlsson, Ryan G Coleman, Vincent Setola, John J Irwin, Hao Fan, Avner Schlessinger, Andrej Sali, Bryan L Roth, Brian K Shoichet. Ligand discovery from a dopamine D3 receptor homology model and crystal structure. Nature Chemical Biology 2011, 7 (11) , 769-778. https://doi.org/10.1038/nchembio.662
    78. Christofer S. Tautermann. The use of G-protein coupled receptor models in lead optimization. Future Medicinal Chemistry 2011, 3 (6) , 709-721. https://doi.org/10.4155/fmc.11.24
    79. Gregory L Wilson, Markus A Lill. Integrating structure-based and ligand-based approaches for computational drug design. Future Medicinal Chemistry 2011, 3 (6) , 735-750. https://doi.org/10.4155/fmc.11.18
    80. Shalinee Dhayal, Noel G Morgan. Pharmacological characterization of the cytoprotective effects of polyunsaturated fatty acids in insulin-secreting BRIN-BD11 cells. British Journal of Pharmacology 2011, 162 (6) , 1340-1350. https://doi.org/10.1111/j.1476-5381.2010.01145.x
    81. Santiago Vilar, Giulio Ferino, Sharangdhar S. Phatak, Barkin Berk, Claudio N. Cavasotto, Stefano Costanzi. Docking-based virtual screening for ligands of G protein-coupled receptors: Not only crystal structures but also in silico models. Journal of Molecular Graphics and Modelling 2011, 29 (5) , 614-623. https://doi.org/10.1016/j.jmgm.2010.11.005
    82. Róbert Kiss, György M. Keserű. Virtual Screening on Homology Models. 2011, 381-410. https://doi.org/10.1002/9783527633326.ch14
    83. B.D. Hudson, Nicola J. Smith, Graeme Milligan. Experimental Challenges to Targeting Poorly Characterized GPCRs: Uncovering the Therapeutic Potential for Free Fatty Acid Receptors. 2011, 175-218. https://doi.org/10.1016/B978-0-12-385952-5.00006-3
    84. Xiaodong Zhang, Guirui Yan, Yiming Li, Weiliang Zhu, Heyao Wang. DC260126, a small-molecule antagonist of GPR40, improves insulin tolerance but not glucose tolerance in obese Zucker rats. Biomedicine & Pharmacotherapy 2010, 64 (9) , 647-651. https://doi.org/10.1016/j.biopha.2010.06.008
    85. Ingo Muegge, Scott Oloff. Virtual Screening. 2010, 1-46. https://doi.org/10.1002/0471266949.bmc006.pub2
    86. Yvonne C. Martin. Pharmacophores. 2010, 455-480. https://doi.org/10.1002/0471266949.bmc145
    87. Lu Tan, Jose Batista, Jürgen Bajorath. Computational Methodologies for Compound Database Searching that Utilize Experimental Protein-Ligand Interaction Information. Chemical Biology & Drug Design 2010, 11 , no-no. https://doi.org/10.1111/j.1747-0285.2010.01007.x
    88. Shao-Yong Lu, Yong-Jun Jiang, Jing Lv, Tian-Xing Wu, Qing-Sen Yu, Wei-Liang Zhu. Molecular docking and molecular dynamics simulation studies of GPR40 receptor–agonist interactions. Journal of Molecular Graphics and Modelling 2010, 28 (8) , 766-774. https://doi.org/10.1016/j.jmgm.2010.02.001
    89. Stephen L. Garland, Frank E. Blaney. GPCR Homology Model Development and Application. 2010, 279-300. https://doi.org/10.1002/0471266949.bmc123
    90. Kyun-Hwan Kim, Nam Doo Kim, Baik-Lin Seong. Pharmacophore-based virtual screening: a review of recent applications. Expert Opinion on Drug Discovery 2010, 5 (3) , 205-222. https://doi.org/10.1517/17460441003592072
    91. Dagmar Stumpfe, Hanna Geppert, Jürgen Bajorath. In Silico Screening. 2010, 73-103. https://doi.org/10.1002/9780470584170.ch3
    92. Changyou Zhou, Cheng Tang, Eric Chang, Min Ge, Songnian Lin, Eric Cline, Carina P. Tan, Yue Feng, Yun-Ping Zhou, George J. Eiermann, Aleksandr Petrov, Gino Salituro, Peter Meinke, Ralph Mosley, Taro E. Akiyama, Monica Einstein, Sanjeev Kumar, Joel Berger, Andrew D. Howard, Nancy Thornberry, Sander G. Mills, Lihu Yang. Discovery of 5-aryloxy-2,4-thiazolidinediones as potent GPR40 agonists. Bioorganic & Medicinal Chemistry Letters 2010, 20 (3) , 1298-1301. https://doi.org/10.1016/j.bmcl.2009.10.052
    93. Irina G. Tikhonova, Daniel Fourmy. The Family of G Protein-Coupled Receptors: An Example of Membrane Proteins. 2010, 441-454. https://doi.org/10.1007/978-1-60761-762-4_23
    94. Petrine Wellendorph, Lars Dan Johansen, Hans Bräuner-Osborne. The Emerging Role of Promiscuous 7TM Receptors as Chemosensors for Food Intake. 2010, 151-184. https://doi.org/10.1016/B978-0-12-381517-0.00005-9
    95. Hui Hu, Ling yan He, Zhen Gong, Ning Li, Yi na Lu, Qi wei Zhai, Hong Liu, Hua liang Jiang, Wei liang Zhu, He yao Wang. A novel class of antagonists for the FFAs receptor GPR40. Biochemical and Biophysical Research Communications 2009, 390 (3) , 557-563. https://doi.org/10.1016/j.bbrc.2009.10.004
    96. Stefano Costanzi, Irina G. Tikhonova, T. Kendall Harden, Kenneth A. Jacobson. Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands. Journal of Computer-Aided Molecular Design 2009, 23 (11) , 747-754. https://doi.org/10.1007/s10822-008-9218-3
    97. Petrine Wellendorph, Lars Dan Johansen, Hans Bräuner-Osborne. Molecular Pharmacology of Promiscuous Seven Transmembrane Receptors Sensing Organic Nutrients. Molecular Pharmacology 2009, 76 (3) , 453-465. https://doi.org/10.1124/mol.109.055244
    98. Graeme Milligan, Leigh A. Stoddart, Nicola J. Smith. Agonism and allosterism: the pharmacology of the free fatty acid receptors FFA2 and FFA3. British Journal of Pharmacology 2009, 158 (1) , 146-153. https://doi.org/10.1111/j.1476-5381.2009.00421.x
    99. Peter Kolb, Rafaela S Ferreira, John J Irwin, Brian K Shoichet. Docking and chemoinformatic screens for new ligands and targets. Current Opinion in Biotechnology 2009, 20 (4) , 429-436. https://doi.org/10.1016/j.copbio.2009.08.003
    100. Lu Tan, Jürgen Bajorath. Utilizing Target-Ligand Interaction Information in Fingerprint Searching for Ligands of Related Targets. Chemical Biology & Drug Design 2009, 74 (1) , 25-32. https://doi.org/10.1111/j.1747-0285.2009.00829.x
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