Choosing the Optimal Rigid Receptor for Docking and Scoring in the CSAR 2013/2014 Experiment

Journal of Chemical Information and Modeling

Volumn 56, Issue 6, 2016, Pages 1004-1012

  Baumgartner, Matthew P ^a   Camacho, Carlos J ^a  

^a UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEINS;

BINDING COMPOUNDS; COMMUNITY STRUCTURES; COMPLEX STRUCTURE; COMPUTATIONAL APPROACH; CORRELATION COEFFICIENT; METHYLTRANSFERASES; MULTIPLE RECEPTORS; SCORING FUNCTIONS;

COMPUTATIONAL METHODS;

BLOOD CLOTTING FACTOR 10A; DRUG; LIGAND; PROTEIN; PROTEIN BINDING; PROTEIN KINASE SYK; TRANSFER RNA METHYLTRANSFERASE;

ALGORITHM; CHEMISTRY; DRUG DESIGN; METABOLISM; MOLECULAR DOCKING; PROTEIN CONFORMATION; STRUCTURE ACTIVITY RELATION;

ALGORITHMS; DRUG DESIGN; FACTOR XA; LIGANDS; MOLECULAR DOCKING SIMULATION; PHARMACEUTICAL PREPARATIONS; PROTEIN BINDING; PROTEIN CONFORMATION; PROTEINS; STRUCTURE-ACTIVITY RELATIONSHIP; SYK KINASE; TRNA METHYLTRANSFERASES;

EID: 84976469356     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/acs.jcim.5b00338     Document Type: Article

References (43)

1. Koes, D.; Khoury, K.; Huang, Y.; Wang, W.; Bista, M.; Popowicz, G. M.; Wolf, S.; Holak, T. A.; Domling, A.; Camacho, C. J. Enabling Large-Scale Design, Synthesis and Validation of Small Molecule Protein-Protein Antagonists PLoS One 2012, 7, e32839 10.1371/journal.pone.0032839
2. Koes, D. R.; Camacho, C. J. Pharmer: Efficient and Exact Pharmacophore Search J. Chem. Inf. Model. 2011, 51, 1307-1314 10.1021/ci200097m
3. Koes, D. R.; Camacho, C. J. Zincpharmer: Pharmacophore Search of the Zinc Database Nucleic Acids Res. 2012, 40, W409-414 10.1093/nar/gks378
4. Koes, D. R.; Camacho, C. J. Pocketquery: Protein-Protein Interaction Inhibitor Starting Points from Protein-Protein Interaction Structure Nucleic Acids Res. 2012, 40, W387-392 10.1093/nar/gks336
5. McGaughey, G. B.; Sheridan, R. P.; Bayly, C. I.; Culberson, J. C.; Kreatsoulas, C.; Lindsley, S.; Maiorov, V.; Truchon, J. F.; Cornell, W. D. Comparison of Topological, Shape, and Docking Methods in Virtual Screening J. Chem. Inf. Model. 2007, 47, 1504-1519 10.1021/ci700052x
6. Jorgensen, W. L. The Many Roles of Computation in Drug Discovery Science 2004, 303, 1813-1818 10.1126/science.1096361
7. Heikamp, K.; Bajorath, J. The Future of Virtual Compound Screening Chem. Biol. Drug Des. 2013, 81, 33-40 10.1111/cbdd.12054
8. Koes, D. R.; Baumgartner, M. P.; Camacho, C. J. Lessons Learned in Empirical Scoring with Smina from the Csar 2011 Benchmarking Exercise J. Chem. Inf. Model. 2013, 53, 1893-1904 10.1021/ci300604z
9. Kitchen, D. B.; Decornez, H.; Furr, J. R.; Bajorath, J. Docking and Scoring in Virtual Screening for Drug Discovery: Methods and Applications Nat. Rev. Drug Discovery 2004, 3, 935-949 10.1038/nrd1549
10. Taminau, J.; Thijs, G.; De Winter, H. Pharao: Pharmacophore Alignment and Optimization J. Mol. Graphics Modell. 2008, 27, 161-169 10.1016/j.jmgm.2008.04.003
11. Sanders, M. P.; Verhoeven, S.; de Graaf, C.; Roumen, L.; Vroling, B.; Nabuurs, S. B.; de Vlieg, J.; Klomp, J. P. Snooker: A Structure-Based Pharmacophore Generation Tool Applied to Class a Gpcrs J. Chem. Inf. Model. 2011, 51, 2277-2292 10.1021/ci200088d
12. 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 10.1021/ci049885e
13. Huey, R.; Morris, G. M.; Olson, A. J.; Goodsell, D. S. A Semiempirical Free Energy Force Field with Charge-Based Desolvation J. Comput. Chem. 2007, 28, 1145-1152 10.1002/jcc.20634
14. Ewing, T. J.; Makino, S.; Skillman, A. G.; Kuntz, I. D. Dock 4.0: Search Strategies for Automated Molecular Docking of Flexible Molecule Databases J. Comput.-Aided Mol. Des. 2001, 15, 411-428 10.1023/A:1011115820450
15. Friesner, R. A.; Banks, J. L.; Murphy, R. B.; Halgren, T. A.; Klicic, J. J.; Mainz, D. T.; Repasky, M. P.; Knoll, E. H.; Shelley, M.; Perry, J. K.; Shaw, D. E.; Francis, P.; Shenkin, P. S. Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy J. Med. Chem. 2004, 47, 1739-1749 10.1021/jm0306430
16. Cheng, T.; Li, X.; Li, Y.; Liu, Z.; Wang, R. Comparative Assessment of Scoring Functions on a Diverse Test Set J. Chem. Inf. Model. 2009, 49, 1079-1093 10.1021/ci9000053
17. Smith, R. D.; Dunbar, J. B., Jr.; Ung, P. M.; Esposito, E. X.; Yang, C. Y.; Wang, S.; Carlson, H. A. Csar Benchmark Exercise of 2010: Combined Evaluation across All Submitted Scoring Functions J. Chem. Inf. Model. 2011, 51, 2115-2131 10.1021/ci200269q
18. Gkeka, P.; Eleftheratos, S.; Kolocouris, A.; Cournia, Z. Free Energy Calculations Reveal the Origin of Binding Preference for Aminoadamantane Blockers of Influenza a/M2tm Pore J. Chem. Theory Comput. 2013, 9, 1272-1281 10.1021/ct300899n
19. Roy, A.; Kucukural, A.; Zhang, Y. I-Tasser: A Unified Platform for Automated Protein Structure and Function Prediction Nat. Protoc. 2010, 5, 725-738 10.1038/nprot.2010.5
20. Wallner, B.; Elofsson, A. All Are Not Equal: A Benchmark of Different Homology Modeling Programs Protein Sci. 2005, 14, 1315-1327 10.1110/ps.041253405
21. Chung, S. Y.; Subbiah, S. A Structural Explanation for the Twilight Zone of Protein Sequence Homology Structure 1996, 4, 1123-1127 10.1016/S0969-2126(96)00119-0
22. Flores, T. P.; Orengo, C. A.; Moss, D. S.; Thornton, J. M. Comparison of Conformational Characteristics in Structurally Similar Protein Pairs Protein Sci. 1993, 2, 1811-1826 10.1002/pro.5560021104
23. Sinko, W.; Lindert, S.; McCammon, J. A. Accounting for Receptor Flexibility and Enhanced Sampling Methods in Computer-Aided Drug Design Chem. Biol. Drug Des. 2013, 81, 41-49 10.1111/cbdd.12051
24. Bottegoni, G.; Kufareva, I.; Totrov, M.; Abagyan, R. Four-Dimensional Docking: A Fast and Accurate Account of Discrete Receptor Flexibility in Ligand Docking J. Med. Chem. 2009, 52, 397-406 10.1021/jm8009958
25. Carlson, H. A.; McCammon, J. A. Accommodating Protein Flexibility in Computational Drug Design Mol. Pharmacol. 2000, 57, 213-218
26. Leach, A. R. Ligand Docking to Proteins with Discrete Side-Chain Flexibility J. Mol. Biol. 1994, 235, 345-356 10.1016/S0022-2836(05)80038-5
27. Morris, G. M.; Huey, R.; Lindstrom, W.; Sanner, M. F.; Belew, R. K.; Goodsell, D. S.; Olson, A. J. Autodock4 and Autodocktools4: Automated Docking with Selective Receptor Flexibility J. Comput. Chem. 2009, 30, 2785-2791 10.1002/jcc.21256
28. 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. 2009, 31, 455-461 10.1002/jcc.21334
29. Yang, J.; Yan, R.; Roy, A.; Xu, D.; Poisson, J.; Zhang, Y. The I-Tasser Suite: Protein Structure and Function Prediction Nat. Methods 2014, 12, 7-8 10.1038/nmeth.3213
30. Zhang, Y. I-Tasser Server for Protein 3d Structure Prediction BMC Bioinf. 2008, 9, 40 10.1186/1471-2105-9-40
31. Le Guilloux, V.; Schmidtke, P.; Tuffery, P. Fpocket: An Open Source Platform for Ligand Pocket Detection BMC Bioinf. 2009, 10, 168 10.1186/1471-2105-10-168
32. Waterhouse, A. M.; Procter, J. B.; Martin, D. M.; Clamp, M.; Barton, G. J. Jalview Version 2 - a Multiple Sequence Alignment Editor and Analysis Workbench Bioinformatics 2009, 25, 1189-1191 10.1093/bioinformatics/btp033
33. Sievers, F.; Wilm, A.; Dineen, D.; Gibson, T. J.; Karplus, K.; Li, W.; Lopez, R.; McWilliam, H.; Remmert, M.; Soding, J.; Thompson, J. D.; Higgins, D. G. Fast, Scalable Generation of High-Quality Protein Multiple Sequence Alignments Using Clustal Omega Mol. Syst. Biol. 2014, 7, 539 10.1038/msb.2011.75
34. Dunbar, J. B., Jr.; Smith, R. D.; Yang, C. Y.; Ung, P. M.; Lexa, K. W.; Khazanov, N. A.; Stuckey, J. A.; Wang, S.; Carlson, H. A. Csar Benchmark Exercise of 2010: Selection of the Protein-Ligand Complexes J. Chem. Inf. Model. 2011, 51, 2036-2046 10.1021/ci200082t
35. Hawkins, P. C.; 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. 2010, 50, 572-584 10.1021/ci100031x
36. Obfit, 2.3.90; OpenBabel, 2015.
37. Balius, T. E.; Mukherjee, S.; Rizzo, R. C. Implementation and Evaluation of a Docking-Rescoring Method Using Molecular Footprint Comparisons J. Comput. Chem. 2011, 32, 2273-2289 10.1002/jcc.21814
38. Tosco, P.; Balle, T.; Shiri, F. Open3dalign: An Open-Source Software Aimed at Unsupervised Ligand Alignment J. Comput.-Aided Mol. Des. 2011, 25, 777-783 10.1007/s10822-011-9462-9
39. Schmidtke, P.; Le Guilloux, V.; Maupetit, J.; Tuffery, P. Fpocket: Online Tools for Protein Ensemble Pocket Detection and Tracking Nucleic Acids Res. 2010, 38, W582-589 10.1093/nar/gkq383
40. O'Boyle, N. M.; Banck, M.; James, C. A.; Morley, C.; Vandermeersch, T.; Hutchison, G. R. Open Babel: An Open Chemical Toolbox J. Cheminf. 2011, 3, 33 10.1186/1758-2946-3-33
41. Johnson, D. K.; Karanicolas, J. Druggable Protein Interaction Sites Are More Predisposed to Surface Pocket Formation Than the Rest of the Protein Surface PLoS Comput. Biol. 2013, 9, e1002951 10.1371/journal.pcbi.1002951
42. Prasad, J. C.; Goldstone, J. V.; Camacho, C. J.; Vajda, S.; Stegeman, J. J. Ensemble Modeling of Substrate Binding to Cytochromes P450: Analysis of Catalytic Differences between Cyp1a Orthologs Biochemistry 2007, 46, 2640-2654 10.1021/bi062320m
43. Bowman, A. L.; Nikolovska-Coleska, Z.; Zhong, H.; Wang, S.; Carlson, H. A. Small Molecule Inhibitors of the Mdm2-P53 Interaction Discovered by Ensemble-Based Receptor Models J. Am. Chem. Soc. 2007, 129, 12809-12814 10.1021/ja073687x