Computational design of ligand-binding membrane receptors with high selectivity

Nature Chemical Biology

Volumn 13, Issue 7, 2017, Pages 715-723

  Feng, Xiang ^a   Ambia, Joaquin ^a,b   Chen, Kuang Yui M ^a,c   Young, Melvin ^a   Barth, Patrick ^a  

^a BAYLOR COLLEGE OF MEDICINE   (United States)

^b The University of Texas at Austin   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DOPAMINE 2 RECEPTOR; DOPAMINE 3 RECEPTOR; ERGOTAMINE; G PROTEIN COUPLED RECEPTOR; LIGAND; MEMBRANE RECEPTOR; SEROTONIN 1B RECEPTOR; SEROTONIN 2B RECEPTOR; DOPAMINE RECEPTOR;

ARTICLE; BINDING SITE; CONFORMATION; DRUG RECEPTOR BINDING; PRIORITY JOURNAL; PROTEIN STRUCTURE; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER AIDED DESIGN; ENZYME SPECIFICITY; HUMAN; METABOLISM; MOLECULAR MODEL; STRUCTURE ACTIVITY RELATION; X RAY CRYSTALLOGRAPHY;

BINDING SITES; COMPUTER-AIDED DESIGN; CRYSTALLOGRAPHY, X-RAY; HUMANS; LIGANDS; MODELS, MOLECULAR; MOLECULAR STRUCTURE; RECEPTORS, DOPAMINE; STRUCTURE-ACTIVITY RELATIONSHIP; SUBSTRATE SPECIFICITY;

EID: 85018309589     PISSN: 15524450     EISSN: 15524469     Source Type: Journal    
DOI: 10.1038/nchembio.2371     Document Type: Article

References (49)

1. Kolb, P. et al. Structure-based discovery of 2-adrenergic receptor ligands. Proc. Natl. Acad. Sci. USA 106, 6843-6848 (2009).
2. Deupi, X. & Kobilka, B. K. Energy landscapes as a tool to integrate GPCR structure, dynamics, and function. Physiology (Bethesda) 25, 293-303 (2010).
3. Katritch, V., Cherezov, V. & Stevens, R. C. Diversity and modularity of G protein-coupled receptor structures. Trends Pharmacol. Sci. 33, 17-27 (2012).
4. Manglik, A. et al. Structural insights into the dynamic process of 2-adrenergic receptor signaling. Cell 161, 1101-1111 (2015).
5. Nygaard, R. et al. The dynamic process of (2)-adrenergic receptor activation. Cell 152, 532-542 (2013).
6. Kahsai, A. W. et al. Multiple ligand-specific conformations of the 2-adrenergic receptor. Nat. Chem. Biol. 7, 692-700 (2011).
7. Katritch, V., Cherezov, V. & Stevens, R. C. Structure-function of the G-protein-coupled receptor superfamily. Annu. Rev. Pharmacol. Toxicol. 53, 531-556 (2013).
8. Kim, T. H. et al. The role of ligands on the equilibria between functional states of a G-protein-coupled receptor. J. Am. Chem. Soc. 135, 9465-9474 (2013).
9. Stevens, R. C. et al. The GPCR Network: A large-scale collaboration to determine human GPCR structure and function. Nat. Rev. Drug Discov. 12, 25-34 (2013).
10. Pieper, U. et al. Coordinating the impact of structural genomics on the human-helical transmembrane proteome. Nat. Struct. Mol. Biol. 20, 135-138 (2013).
11. Eswar, N., Eramian, D., Webb, B., Shen, M. Y. & Sali, A. Protein structure modeling with MODELLER. Methods Mol. Biol. 426, 145-159 (2008).
12. Kelm, S., Shi, J. & Deane, C. M. MEDELLER: homology-based coordinate generation for membrane proteins. Bioinformatics 26, 2833-2840 (2010).
13. Chen, K. Y., Sun, J., Salvo, J. S., Baker, D. & Barth, P. High-resolution modeling of transmembrane helical protein structures from distant homologues. PLoS Comput. Biol. 10, e1003636 (2014).
14. Yang, J. et al. The I-TASSER Suite: protein structure and function prediction. Nat. Methods 12, 7-8 (2015).
15. Davis, I. W. & Baker, D. RosettaLigand docking with full ligand and receptor flexibility. J. Mol. Biol. 385, 381-392 (2009).
16. Repasky, M. P., Shelley, M. & Friesner, R. A. in Current Protocols in Bioinformatics. Ch. 8, Unit 8. 12 (John Wiley and Sons, Inc., 2007).
17. Zhou, Z., Felts, A. K., Friesner, R. A. & Levy, R. M. Comparative performance of several flexible docking programs and scoring functions: enrichment studies for a diverse set of pharmaceutically relevant targets. J. Chem. Inf. Model. 47, 1599-1608 (2007).
18. Moustakas, D. T. et al. Development and validation of a modular, extensible docking program: DOCK 5. J. Comput. Aided Mol. Des. 20, 601-619 (2006).
19. Trott, O. & Olson, A. J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem. 31, 455-461 (2010).
20. Huang, X. P. et al. Allosteric ligands for the pharmacologically dark receptors GPR68 and GPR65. Nature 527, 477-483 (2015).
21. Michino, M. et al. Community-wide assessment of GPCR structure modelling and ligand docking: GPCR Dock 2008. Nat. Rev. Drug Discov. 8, 455-463 (2009).
22. Kufareva, I., Rueda, M., Katritch, V., Stevens, R. C. & Abagyan, R. Status of GPCR modeling and docking as reflected by community-wide GPCR Dock 2010 assessment. Structure 19, 1108-1126 (2011).
23. Kufareva, I., Katritch, V., Stevens, R. C. & Abagyan, R. Advances in GPCR modeling evaluated by the GPCR Dock 2013 assessment: meeting new challenges. Structure 22, 1120-1139 (2014).
24. Forrest, L. R., Tang, C. L. & Honig, B. On the accuracy of homology modeling and sequence alignment methods applied to membrane proteins. Biophys. J. 91, 508-517 (2006).
25. Stamm, M. & Forrest, L. R. Structure alignment of membrane proteins: Accuracy of available tools and a consensus strategy. Proteins 83, 1720-1732 (2015).
26. Qian, B. et al. High-resolution structure prediction and the crystallographic phase problem. Nature 450, 259-264 (2007).
27. Combs, S. A. et al. Small-molecule ligand docking into comparative models with Rosetta. Nat. Protoc. 8, 1277-1298 (2013).
28. Fischer, M., Coleman, R. G., Fraser, J. S. & Shoichet, B. K. Incorporation of protein flexibility and conformational energy penalties in docking screens to improve ligand discovery. Nat. Chem. 6, 575-583 (2014).
29. Spyrakis, F., BidonChanal, A., Barril, X. & Luque, F. J. Protein flexibility and ligand recognition: challenges for molecular modeling. Curr. Top. Med. Chem. 11, 192-210 (2011).
30. Cavasotto, C. N. & Abagyan, R. A. Protein flexibility in ligand docking and virtual screening to protein kinases. J. Mol. Biol. 337, 209-225 (2004).
31. Conklin, B. R. et al. Engineering GPCR signaling pathways with RASSLs. Nat. Methods 5, 673-678 (2008).
32. Roth, B. L. DREADDs for neuroscientists. Neuron 89, 683-694 (2016).
33. Nguyen, E. D., Norn, C., Frimurer, T. M. & Meiler, J. Assessment and challenges of ligand docking into comparative models of G-protein-coupled receptors. PLoS One 8, e67302 (2013).
34. Rodriguez, G. J., Yao, R., Lichtarge, O. & Wensel, T. G. Evolution-guided discovery and recoding of allosteric pathway specificity determinants in psychoactive bioamine receptors. Proc. Natl. Acad. Sci. USA 107, 7787-7792 (2010).
35. Liu, T., Lin, Y., Wen, X., Jorissen, R. N. & Gilson, M. K. BindingDB: A web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res. 35, D198-D201 (2007).
36. Wang, C. et al. Structural basis for molecular recognition at serotonin receptors. Science 340, 610-614 (2013).
37. Barth, P., Schonbrun, J. & Baker, D. Toward high-resolution prediction and design of transmembrane helical protein structures. Proc. Natl. Acad. Sci. USA 104, 15682-15687 (2007).
38. Lemmon, G. & Meiler, J. Towards ligand docking including explicit interface water molecules. PLoS One 8, e67536 (2013).
39. Söding, J., Biegert, A. & Lupas, A. N. The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res. 33, W244-W248 (2005).
40. Isberg, V. et al. GPCRdb: An information system for G-protein-coupled receptors. Nucleic Acids Res. 44, D1, D356-D364 (2016).
41. Isberg, V. et al. GPCRDB: An information system for G-protein-coupled receptors. Nucleic Acids Res. 42, D422-D425 (2014).
42. Yarov-Yarovoy, V., Schonbrun, J. & Baker, D. Multipass membrane protein structure prediction using Rosetta. Proteins 62, 1010-1025 (2006).
43. Tibshirani, R., Walther, G. & Hastie, T. Estimating the number of data clusters via the Gap statistic. J. R. Statist. Soc. B 63, 411-423 (2001).
44. Hawkins, P. C. D., Skillman, A. G., Warren, G. L., Ellingson, B. A. & Stahl, M. T. Conformer generation with OMEGA: Algorithm and validation using high quality structures from the Protein Databank and Cambridge Structural Database. J. Chem. Inf. Model. 50, 572-584 (2010).
45. Venkatakrishnan, A. J. et al. Molecular signatures of G-protein-coupled receptors. Nature 494, 185-194 (2013).
46. Tinberg, C. E. et al. Computational design of ligand-binding proteins with high affinity and selectivity. Nature 501, 212-216 (2013).
47. Chen, K. Y., Zhou, F., Fryszczyn, B. G. & Barth, P. Naturally evolved G-protein-coupled receptors adopt metastable conformations. Proc. Natl. Acad. Sci. USA 109, 13284-13289 (2012).
48. Luo, J., Zhu, Y., Zhu, M. X. & Hu, H. Cell-based calcium assay for medium to high throughput screening of TRP channel functions using FlexStation 3. J. Vis. Exp. http://dx. doi. org/10. 3791/3149 (2011).
49. Sung, Y. M., Wilkins, A. D., Rodriguez, G. J., Wensel, T. G. & Lichtarge, O. Intramolecular allosteric communication in dopamine D2 receptor revealed by evolutionary amino acid covariation. Proc. Natl. Acad. Sci. USA 113, 3539-3544 (2016).