Novel statistical-thermodynamic methods to predict protein-ligand binding positions using probability distribution functions

Proteins: Structure, Function and Genetics

Volumn 62, Issue 1, 2006, Pages 202-208

  Ruvinsky, A M ^a,b   Kozintsev, A V ^a  

^a Algodign LLC   (Russian Federation)

^b Force Field Laboratory   (Russian Federation)

Author keywords

Cluster; Docking; Probability distribution function; Protein ligand binding

Indexed keywords

ALGORITHM; ANALYTIC METHOD; ARTICLE; CLUSTER ANALYSIS; COMPLEX FORMATION; ENZYME ACTIVE SITE; LIGAND BINDING; PREDICTION; PRIORITY JOURNAL; PROBABILITY; PROTEIN BINDING; PROTEIN FUNCTION; RECEPTOR OCCUPANCY; THERMODYNAMICS;

BINDING SITES; LIGANDS; MODELS, MOLECULAR; MODELS, THEORETICAL; PROBABILITY; PROTEIN BINDING; PROTEINS; SOFTWARE; THERMODYNAMICS;

EID: 30344467833     PISSN: 08873585     EISSN: None     Source Type: Journal    
DOI: 10.1002/prot.20673     Document Type: Article

References (36)

1. Stockwell BR. Exploring biology with small organic molecules. Nature 2004;432:846-854.
2. Shoichet BK. Virtual screening of chemical libraries. Nature 2004;432:862-865.
3. Brooijmans N, Kuntz I. Molecular recognition and docking algorithms. Annu Rev Biophys Biomol Struct 2003;32:335-373.
4. Halperin I, Ma B, Wolfson H, Nussinov R. Principles of docking: an overview of search algorithms and a guide to scoring functions. Prot Str Func Gen 2002;47:409-443.
5. Gohlke H, Klebe G. Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors. Angew Chem Int Ed 2002;41:2644-2676.
6. Taylor RD, Jewsbury PJ, Essex JW. A review of protein-small molecule docking methods. J Comp Aid Mol Design 2002;16:151-166.
7. Ajay, Murcko MA. Computational methods to predict binding free energy in ligand-receptor complexes. J Med Chem 1995;38:4953-4967.
8. Gilson MK, Given JA, Head MS. A new class of models for computing receptor-ligand binding affinities. Chem Biol 1997;4:87-92.
9. Mackerell AD. Empirical force fields for biological macromolecules: overview and issues. J Comp Chem 2004;25:1584-1604.
10. Bissantz C, Folkers G, Rognan D. Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. J Med Chem 2000;43:4759-4767.
11. Stahl M, Rarey M. Detailed analysis of scoring functions for virtual screening. J Med Chem 2001;44:1035-1042.
12. Perez C, Ortiz AR. Evaluation of docking functions for protein-ligand docking. J Med Chem 2001;44:3768-3785.
13. Wang R, Lu Y, Wang S. Comparative evaluation of 11 scoring functions for molecular docking. J Med Chem 2003;46:2287-2303.
14. Kellenberger E, Rodrigo J, Muller P, Rognan D. Comparative evaluation of eight docking tools for docking and virtual screening accuracy. Prot Str Funct Bio 2004;57:225-242.
15. Kontoyianni M, McClellan LM, Sokol GS. Evaluation of docking performance: comparative data on docking algorithms. J Med Chem 2004;47:558-565.
16. Wang W, Donini O, Reyes CM, Kollman PA. Biomolecular simulations: recent developments in force fields, simulations of enzyme catalysis, protein-ligand, protein-protein, and protein-nucleic acid noncovalent interactions. Annu Rev Biophys Biomol Struct 2001; 30:211-243.
17. Kaplan IG. Theory of molecular interactions. Amsterdam: Elsevier; 1986. 126 p.
18. Dennis S, Kortvelyesi T, Vajda S. Computational mapping identifies the binding sites of organic solvents on proteins. Proc Natl Acad Sci USA 2002;99:4290-4295.
19. Verkhivker GM, Bouzida D, Gehlhaar DK, Rejto PA, Schaffer L, Arthurs S, Colson AB, Freer ST, Larson V, Luty BA, Marrone T, Rose PW. Hierarchy of simulation models in predicting structure and energetics of the Src SH2 domain binding to tyrosyl phosphopeptides. J Med Chem 2002;45:72-89.
20. Källblad P, Mancera RL, Todorov NP. Assessment of multiple binding modes in ligand-protein docking. J Med Chem 2004;47: 3334-3337.
21. Rosenfeld RJ, Goodsell DS, Musah RA, Morris GM, Goodin DB, Olson AJ. Automated docking of ligands to an artificial active site: augmenting crystallographic analysis with computer modeling. J Comp-Aid Mol Des 2003;17:525-536.
22. Camacho CJ, Gatchell DW. Successful discrimination of protein interactions. Prot Str Funct Gen 2003;52:92-97.
23. Shortle D, Simons KT, Baker D. Clustering of low-energy conformations near native structures of small proteins. Proc Natl Acad Sci USA 1998;95:11158-11162.
24. Bonneau R, Tsai J, Ruczinski I, Chivian D, Rohl C, Strauss CEM, Baker D. Rosetta in CASP4: progress in ab initio protein structure prediction. Prot Str Funct Gen Suppl 2001;5:119-126.
25. Wang K, Fain B, Levitt M, Samudrala R. Improved protein structure selection using decoy-dependent discriminatory functions. BMC Str Biol 2004;4:1-18.
26. Xiang Z, Soto CS, Honig B. Evaluating conformational free energies: the colony energy and its application to the problem of loop prediction. Proc Natl Acad Sci USA 2002;99:7432-7437.
27. Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, Olson AJ. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comp Chem 1998;19:1639-1662,
28. Hendrix DA, Jarzynski C. A "fast growth" method of computing free energy differences. J Chem Phys 2001;114:5974-5981.
29. Finkelstein AV, Janin J. The price of lost freedom: entropy of bimolecular complex formation. Prot Eng 1989;3:1-3.
30. Amzel LM. Loss of translational entropy in binding, folding and catalysis. Prot Str Funct Gen 1997;28:144-149.
31. Hermans J, Wang L. Inclusion of loss of translational and rotational freedom theoretical estimates of free energies of binding. Application to a complex of benzene and mutant T4 lysozyme. J Am Chem Soc 1997;119:2707-2714.
32. Ruvinsky AM. On the calculation of protein-ligand binding constants. Proceed Europ Confer Comp Biol 2003;204-205.
33. Ruvinsky AM, Kozintsev AV. A new and fast statistical-thermodynamic method for computation of protein-ligand binding entropy substantially improves docking accuracy. J Comp Chem 2005;26:1089-1095.
34. Rumer YuB, Ryvkin MSh. Thermodynamics, statistical physics and kinetics. Moscow. Mir Publishers; 1980. 128 p, Book Chapter II.
35. Ruvinsky AM, Kozintsev AV. The key role of atom types, reference states and interaction cutoff radii in the knowledge-based method: new variational approach. Prot Struct Funct Bioinf 2005;58:845-854.
36. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The Protein Data Bank. Nucleic Acids Res 2000;28:235-242.