Robust scoring functions for protein-ligand interactions with quantum chemical charge models

Journal of Chemical Information and Modeling

Volumn 51, Issue 10, 2011, Pages 2528-2537

  Wang, Jui Chih ^a   Lin, Jung Hsin ^a,b,c   Chen, Chung Ming ^a   Perryman, Alex L ^d   Olson, Arthur J ^d  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b RESEARCH CENTER FOR APPLIED SCIENCES   (Taiwan)

^c INSTITUTE OF BIOMEDICAL SCIENCES   (Taiwan)

^d SCRIPPS RESEARCH INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION REACTIONS; ELECTROSTATICS; FREE ENERGY; LIGANDS; MEAN SQUARE ERROR; PROTEINS; REGRESSION ANALYSIS; STATISTICS;

ATOMIC PARTIAL CHARGES; ELECTROSTATIC POTENTIALS; ORDINARY LEAST SQUARES; PROTEIN-LIGAND INTERACTIONS; QUANTUM CHEMICAL APPROACH; ROOT MEAN SQUARED DEVIATIONS; ROOT MEAN SQUARED ERRORS; STATISTICAL PERFORMANCE;

QUANTUM CHEMISTRY;

LIGAND; PROTEIN;

ALGORITHM; ARTICLE; CHEMISTRY; CONFORMATION; METABOLISM; MOLECULAR DYNAMICS; PROTEIN BINDING; QUANTITATIVE STRUCTURE ACTIVITY RELATION; QUANTUM THEORY; REGRESSION ANALYSIS; STATIC ELECTRICITY; THERMODYNAMICS;

ALGORITHMS; LEAST-SQUARES ANALYSIS; LIGANDS; MOLECULAR CONFORMATION; MOLECULAR DYNAMICS SIMULATION; PROTEIN BINDING; PROTEINS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; QUANTUM THEORY; STATIC ELECTRICITY; THERMODYNAMICS;

EID: 80054928964     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci200220v     Document Type: Article

References (59)

1. Gilson, M. K.; Zhou, H. X. Calculation of protein-ligand binding affinities Annu. Rev. Biophys. Biomol. Struct. 2007, 36, 21-42 (Pubitemid 46998108)
2. Gilson, M. K.; Given, J. A.; Bush, B. L.; McCammon, J. A. The statistical-thermodynamic basis for computation of binding affinities: A critical review Biophys. J. 1997, 72, 1047-1069 (Pubitemid 27113632)
3. Eldridge, M. D.; Murray, C. W.; Auton, T. R.; Paolini, G. V.; Mee, R. P. Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes J. Comput.-Aided Mol. Des. 1997, 11, 425-445 (Pubitemid 127505895)
4. Sotriffer, C. A.; Sanschagrin, P.; Matter, H.; Klebe, G. SFCscore: Scoring functions for affinity prediction of protein-ligand complexes Proteins: Struct., Funct., Bioinf. 2008, 73, 395-419
5. Das, S.; Krein, M. P.; Breneman, C. M. Binding affinity prediction with property-encoded shape distribution signatures J. Chem. Inf. Model. 2010, 50, 298-308
6. Kramer, C.; Gedeck, P. Global Free Energy Scoring Functions Based on Distance-Dependent Atom-Type Pair Descriptors J. Chem. Inf. Model. 2011, 51, 707-720
7. Hansch, C.; Maloney, P. P.; Fujita, T. Correlation of biological activity of phenoxyacetic acids with hammett substituent constants and partition coefficients Nature 1962, 194, 178-180
8. Morris, G. M.; Goodsell, D. S.; Halliday, R. S.; Huey, R.; Hart, W. E.; Belew, R. K.; Olson, A. J. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function J. Comput. Chem. 1998, 19, 1639-1662 (Pubitemid 128590223)
9. 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 (Pubitemid 46506716)
10. Raha, K.; Merz, K. M. Large-scale validation of a quantum mechanics based scoring function: Predicting the binding affinity and the binding mode of a diverse set of protein-ligand complexes J. Med. Chem. 2005, 48, 4558-4575 (Pubitemid 40993417)
11. Brooijmans, N.; Kuntz, I. D. Molecular recognition and docking algorithms Annu. Rev. Biophys. Biomol. Struct. 2003, 32, 335-373 (Pubitemid 37056233)
12. Lin, J. H. Accommodating protein flexibility for structure-based drug design Curr. Top. Med. Chem. 2011, 11, 171-178
13. Lin, J. H.; Perryman, A. L.; Schames, J. R.; McCammon, J. A. Computational drug design accommodating receptor flexibility: The relaxed complex scheme J. Am. Chem. Soc. 2002, 124, 5632-5633 (Pubitemid 34533490)
14. Lin, J. H.; Perryman, A. L.; Schames, J. R.; McCammon, J. A. The relaxed complex method: Accommodating receptor flexibility for drug design with an improved scoring scheme Biopolymers 2003, 68, 47-62 (Pubitemid 36098307)
15. Hawkins, D. M. The problem of overfitting J. Chem. Inf. Comput. Sci. 2004, 44, 1-12
16. Rogers, D.; Hopfinger, A. J. Application of genetic function approximation to quantitative structure-activity-relationships and quantitative structure-property relationships J. Chem. Inf. Comput. Sci. 1994, 34, 854-866
17. Gasteiger, J.; Marsili, M. Iterative partial equalization of orbital electronegativity-A rapid access to atomic charges Tetrahedron 1980, 36, 3219-3228
18. Cornell, W. D.; Cieplak, P.; Bayly, C. I.; Gould, I. R.; Merz, K. M.; Ferguson, D. M.; Spellmeyer, D. C.; Fox, T.; Caldwell, J. W.; Kollman, P. A. A second generation force-field for the simulation of proteins, nucleic-acids, and organic-molecules J. Am. Chem. Soc. 1995, 117, 5179-5197
19. o structure, and dipole moment of dimethylsulfoxide Z. Naturforsch. 1964, 19a, 512-514
20. Cho, A. E.; Guallar, V.; Berne, B. J.; Friesner, R. Importance of accurate charges in molecular docking: Quantum mechanical/molecular mechanical (QM/MM) approach J. Comput. Chem. 2005, 26, 915-931 (Pubitemid 40860395)
21. Cho, A. E.; Rinaldo, D. Extension of QM/MM docking and its applications to metalloproteins J. Comput. Chem. 2009, 30, 2609-2616
22. Tsai, K. C.; Wang, S. H.; Hsiao, N. W.; Li, M.; Wang, B. The effect of different electrostatic potentials on docking accuracy: A case study using DOCK5.4 Bioorg. Med. Chem. Lett. 2008, 18, 3509-3512 (Pubitemid 351787573)
23. Konovalov, D. A.; Llewellyn, L. E.; Heyden, Y. V.; Coomans, D. Robust cross-validation of linear regression qsar models J. Chem. Inf. Model. 2008, 48, 2081-2094
24. Wang, J. C.; Lin, J. H. Robust regression analysis of protein-ligand binding free energy models: toward the identification of druggable genomes Int. J. Syst. Syn. Biol. 2010, 1, 339-354
25. Wang, R. X.; Lu, Y. P.; Wang, S. M. Comparative evaluation of 11 scoring functions for molecular docking J. Med. Chem. 2003, 46, 2287-2303
26. Velec, H. F. G.; Gohlke, H.; Klebe, G. DrugScore(CSD)-knowledge-based scoring function derived from small molecule crystal data with superior recognition rate of near-native ligand poses and better affinity prediction J. Med. Chem. 2005, 48, 6296-6303 (Pubitemid 41428984)
27. Xie, Z. R.; Hwang, M. J. An interaction-motif-based scoring function for protein-ligand docking BMC Bioinf. 2010, 11, 298
28. Cheng, T. J.; Li, X.; Li, Y.; Liu, Z. H.; Wang, R. X. Comparative assessment of scoring functions on a diverse test set J. Chem. Inf. Model. 2009, 49, 1079-1093
29. Roche, O.; Kiyama, R.; Brooks, C. L. Ligand-Protein DataBase: Linking protein-ligand complex structures to binding data J. Med. Chem. 2001, 44, 3592-3598 (Pubitemid 33026666)
30. Weiner, S. J.; Kollman, P. A.; Case, D. A.; Singh, U. C.; Ghio, C.; Alagona, G.; Profeta, S.; Weiner, P. A new force-field for molecular mechanical simulation of nucleic-acids and proteins J. Am. Chem. Soc. 1984, 106, 765-784 (Pubitemid 14548426)
31. Mehler, E. L.; Solmajer, T. Electrostatic effects in proteins- comparison of dielectric and charge models Protein Eng. 1991, 4, 903-910
32. Bohm, H. J. The development of a simple empirical scoring function to estimate the binding constant for a protein ligand complex of known 3-dimensional structure J. Comput.-Aided Mol. Des. 1994, 8, 243-256
33. Bayly, C. I.; Cieplak, P.; Cornell, W. D.; Kollman, P. A. A well-behaved electrostatic potential based method using charge restraints for deriving atomic charges-the resp model J. Phys. Chem. 1993, 97, 10269-10280
34. Jakalian, A.; Bush, B. L.; Jack, D. B.; Bayly, C. I. Fast, efficient generation of high-quality atomic Charges. AM1-BCC model: I. Method J. Comput. Chem. 2000, 21, 132-146
35. Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenberg, J. L.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery, Jr., J. A.; Peralta, J. E.; Ogliaro, F.; Bearpark, M.; Heyd, J. J.; Brothers, E.; Kudin, K. N.; Staroverov, V. N.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, N. J.; Klene, M.; Knox, J. E.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Zakrzewski, V. G.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Dapprich, S.; Daniels, A. D.; Farkas, Ö.; Foresman, J. B.; Ortiz, J. V.; Cioslowski, J.; Fox, D. J. Gaussian 09, revision A.02; Gaussian, Inc.: Wallingford, CT, 2009.
36. Hehre, W. J.; Ditchfie., R; Pople, J. A. Self-consistent molecular-orbital Methods. XII. Further extensions of gaussian-type basis sets for use in molecular-orbital studies of organic-molecules J. Chem. Phys. 1972, 56, 2257-2261
37. Jakalian, A.; Jack, D. B.; Bayly, C. I. Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation J. Comput. Chem. 2002, 23, 1623-1641 (Pubitemid 35330860)
38. Ponder, J. W.; Case, D. A. Force fields for protein simulations Adv. Protein Chem. 2003, 66, 27-85 (Pubitemid 37392314)
39. Duan, Y.; Wu, C.; Chowdhury, S.; Lee, M. C.; Xiong, G. M.; Zhang, W.; Yang, R.; Cieplak, P.; Luo, R.; Lee, T.; Caldwell, J.; Wang, J. M.; Kollman, P. A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations J. Comput. Chem. 2003, 24, 1999-2012
40. Guha, R.; Howard, M. T.; Hutchison, G. R.; Murray-Rust, P.; Rzepa, H.; Steinbeck, C.; Wegner, J.; Willighagen, E. L. Blue Obelisk- Interoperability in chemical informatics J. Chem. Inf. Model. 2006, 46, 991-998 (Pubitemid 43999142)
41. Pettersen, E. F.; Goddard, T. D.; Huang, C. C.; Couch, G. S.; Greenblatt, D. M.; Meng, E. C.; Ferrin, T. E. UCSF chimera-A visualization system for exploratory research and analysis J. Comput. Chem. 2004, 25, 1605-1612
42. Autenrieth, F.; Tajkhorshid, E.; Baudry, J.; Luthey-Schulten, Z. Classical force field parameters for the heme prosthetic group of cytochrome c J. Comput. Chem. 2004, 25, 1613-1622
43. Oda, A.; Yamaotsu, N.; Hirono, S. New AMBER force field parameters of heme iron for cytochrome P450s determined by quantum chemical calculations of simplified models J. Comput. Chem. 2005, 26, 818-826 (Pubitemid 40751576)
44. Wesson, L.; Eisenberg, D. Atomic Solvation Parameters Applied to Molecular-Dynamics of Proteins in Solution Protein Sci. 1992, 1, 227-235 (Pubitemid 23007289)
45. Stouten, P. F. W.; Frommel, C.; Nakamura, H.; Sander, C. An Effective Solvation Term Based on Atomic Occupancies for Use in Protein Simulations Mol. Simul. 1993, 10, 97-120
46. Bikadi, Z.; Hazai, E. Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock J. Cheminf. 2009, 1, 15
47. Rousseeuw, P. J. Least Median of Squares Regression J. Am. Stat. Assoc. 1984, 79, 871-880
48. Rousseeuw, P. J.; Leroy, A. M. In Robust Regression and Outlier Detection; Barnett, V., Eds.; John Wiley & Sons, Inc.: Hoboken, NJ, 1987; pp 9-17, 112-142.
49. Rousseeuw, P. J.; Van Driessen, K. Computing LTS regression for large data sets Data Min. Knowl. Dis. 2006, 12, 29-45 (Pubitemid 43255930)
50. Rousseeuw, P.; Croux, C.; Todorov, V.; Ruckstuhl, A.; Salibian-Barrera, M.; Verbeke, T.; Maechler, M. robustbase: Basic Robust Statistics, R package version 0.7-6; Swiss Federal Institute of Technology Zurich: Zurich, Switzerland; http://CRAN.R-project.org/package=robustbase, (accessed August 11, 2011).
51. Wang, R. X.; Lai, L. H.; Wang, S. M. Further development and validation of empirical scoring functions for structure-based binding affinity prediction J. Comput.-Aided Mol. Des. 2002, 16, 11-26
52. Anderson, R. In Modern Methods for Robust Regression; Liao, T. F., Ed.; SAGE: Thousand Oaks, CA, 2008; Chapter 4, pp 67-68.
53. Tukey, J. W. Graphical displays for alternative regression fits. In Robust Statistics and Diagnostics, Part 2; Stahel, W.; Weisberg, S., Eds.; Springer-Verlag: New York, 1991; pp 309.
54. Hawkins, D. M.; Kraker, J. Deterministic fallacies and model validation J. Chemom. 2010, 24, 188-193
55. Shao, J. Linear-Model Selection by Cross-Validation J. Am. Stat. Assoc. 1993, 88, 486-494
56. Golbraikh, A.; Tropsha, A. Beware of q(2)! J. Mol. Graphics Modell. 2002, 20, 269-276
57. Wang, R. X.; Fang, X. L.; Lu, Y. P.; Wang, S. M. The PDBbind database: Collection of binding affinities for protein-ligand complexes with known three-dimensional structures J. Med. Chem. 2004, 47, 2977-2980
58. Wang, R. X.; Fang, X. L.; Lu, Y. P.; Yang, C. Y.; Wang, S. M. The PDBbind database: Methodologies and updates J. Med. Chem. 2005, 48, 4111-4119
59. Wang, R.; Fang, X. X-SCORE; Department of Internal Medicine, University of Michigan Medical School: Ann Arbor, MI; http://sw16.im.med.umich.edu/ software/xtool/, (accessed April 28, 2011).