Computational protocol for predicting the binding affinities of zinc containing metalloprotein-ligand complexes

Proteins: Structure, Function and Genetics

Volumn 67, Issue 4, 2007, Pages 1167-1178

  Jain, Tarun ^a   Jayaram, B ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

Author keywords

Binding affinity; Metalloenzyme; Scoring function; Structure based drug design; Zinc ion

Indexed keywords

METALLOPROTEIN; ZINC;

ARTICLE; BINDING AFFINITY; CHEMICAL INTERACTION; CORRELATION ANALYSIS; DIELECTRIC CONSTANT; ELECTRICITY; ENTROPY; HYDROPHOBICITY; LIGAND BINDING; PRIORITY JOURNAL; PROTEIN BINDING; PROTEIN CONFORMATION; PROTEIN TARGETING;

AMINO ACID MOTIFS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; LIGANDS; METALLOPROTEINS; MOLECULAR STRUCTURE; PROTEIN BINDING; THERMODYNAMICS; ZINC;

EID: 34248596450     PISSN: 08873585     EISSN: 10970134     Source Type: Journal    
DOI: 10.1002/prot.21332     Document Type: Article

References (71)

1. Frausto da Silva JJR, Williams RJP. The biological chemistry of the elements. Oxford: Oxford University Press; 1991.
2. Vallee BL, Auld DS. Functional zinc-binding motifs in exzymes and DNA-binding proteins. Faraday Discuss 1992;93:47-65.
3. Overall CM, Lopez-Otin C. Strategies for MMP inhibition in cancer: innovations for the post-trial era. Nat Rev Cancer 2002;2:657-672.
4. Christianson DW, Fierke CA. Carbonic anhydrase: evolution of the zinc binding site by nature and by design. Acc Chem Res 1996;29:331-339.
5. Quiocho FA, Lipscomb WN. Carboxypeptidase A: a protein and an enzyme. Adv Protein Chem 1971;25:1-49.
6. Branden CI, Eklund H, Nordstrom B, Boiwe T, Soderlund G, Zeppezauer E, Ohlsson I, Åkeson Å. Structure of liver alcohol dehydrogenase at 2.9Å resolution. Proc Natl Acad Sci USA 1973;70:2439-2442.
7. Rao GB. Recent developments in the design of specific matrix metalloproteinase inhibitors aided by structural and computational studies. Curr Pharm Des 2005;11:295-322.
8. Matthews BW. Structural basis of the action of thermolysin and related zinc peptidases. Acc Chem Res 1988;21:333-340.
9. Lipscomb WN, Strater N. Recent advances in zinc enzymology. Chem Rev 1996;96:2375-2434.
10. Yamashita MM, Wesson L, Eisenman G, Eisenberg D. Where metal ions bind in proteins. Proc Natl Acad Sci USA 1990;87: 5648-5652.
11. Dudev T, Lim C. Principles governing Mg, Ca and Zn binding and selectivity in proteins. Chem Rev 2003;103:773-787.
12. Alberts IL, Nadassay K, Wodak SJ. Analysis of zinc binding sites in protein crystal structures. Protein Sci 1998;7:1700-1716.
13. van der Vaart A, Merz KM, Jr. The role of polarization and charge transfer in the salvation of biomolecules. J Am Chem Soc 1999;121:9182-9190.
14. Sakharov D, Lim C. Zn protein simulations including charge transfer and local polarization effects. J Am Chem Soc 2005; 127:4921-4929.
15. Banci L. Molecular dynamics simulations of metalloproteins. Curr Opin Chem Biol 2003;7:143-149.
16. Brothers EN, Suarez D, Deerfield DW, II, Merz KM, Jr. PM3-compatible zinc parameters optimized for metalloenzyme active sites. J Comput Chem 2004;25:1677-1692.
17. Kuntz ID. Structure-based strategies for drug design and discovery. Science 1992;257:1073-1082.
18. Latha N, Jayaram B. A binding affinity based computational pathway for active-site directed lead molecule design: some promises and perspectives. Drug Design Rev Online 2004;2: 145-165.
19. Vedani A, Huhta DW. A new force field for modeling metalloproteins. J Am Chem Soc 1990;112:4759-4767.
20. Vedani A, Dobler M, Dunitz JD. An empirical potential function for metal centers: application to molecular mechanics calculations on metalloproteins. J Comput Chem 1986;7:701-710.
21. Hoops SC, Anderson KW, Merz KM, Jr. Force field design for metalloproteins. J Am Chem Soc 1991;113:8262-8270.
22. Ryde U. Molecular dynamics simulations of alcohol dehydrogenase with a four- or five-coordinate catalytic zinc ion. Proteins: Struct Funct Genet 1995;21:40-56.
23. Stote RH, Karplus M. Zinc binding in proteins and solution: a simple but accurate nonbonded representation. Proteins: Struct Funct Genet 1995;23:12-31.
24. Makinen MW, Troyer JN, van der Werff H, Berendsen JC, van Gunsteren WF. Dynamical structure of carboxypeptidase A. J Mol Biol 1989;207:210-216.
25. Bredenberg J, Nilsson L. Modeling zinc sulfhydryl bonds in zinc fingers. Int J Quantum Chem 2001;83:230-244.
26. Pang YP. Novel zinc protein molecular dynamics simulations: steps towards antiangiogenesis for cancer treatment. J Mol Model 1999;5:196-202.
27. 2+. J Phys Chem B 2001;105:4446-4452.
28. Lin Y, Lim C. Factors governing the protonation state of Zn-bound histidine in proteins: a DFT/CDM study. J Am Chem Soc 2004;126:2602-2612.
29. Garmer DR, Gresh N, Roques BP. Modeling of inhibitor-metalloenzyme interactions and selectivity using molecular mechanics grounded in quantum chemistry. Proteins: Struct Funct Genet 1998;31:42-60.
30. Kitchen DB, Decornez H, Furr JR, Bajorath J. Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 2004;3:935-949.
31. Ajay, Murcko MA. Computational methods to predict binding free energy in ligand-receptor complexes. J Med Chem 1995;38: 4953-4967.
32. Gohlke H, Klebe G. Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptor. Angew Chem Int Ed 2002;41:2644-2676.
33. Brandsdal BO, Osterberg F, Almlof M, Feierberg I, Luzhkov VB, Åqvist J. Free energy calculations and ligand binding. Adv Protein Chem 2003;66:123-158.
34. Wang W, Donini O, Reyes CM, Kollman PA. Biomolecular simulations: recent developments in force fields, simulation of enzyme catalysis, protein-ligand, protein-protein and protein-nucleic acid noncovalent interactions. Annu Rev Biophys Biomol Struct 2001;30:211-243.
35. Williams DH, Cox JPL, Doig AJ, Gardner M, Gerhard U, et al. Toward the semiquantitative estimation of binding constants. Guides for peptide-peptide binding in aqueous solution. J Am Chem Soc 1991;113:7020-7030.
36. Vajda S, Weng Z, Rosenfeld R, DeLisi C. Effect of conformational flexibility and solvation on receptor-ligand binding free energies. Biochemistry 1994;33:13977-13988.
37. Gohlke H, Klebe G. Statistical potential and scoring functions applied to protein-ligand binding. Curr Opin Struct Biol 2001;11: 231-235.
38. Raha K, Merz KM, Jr. 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 comglexes. J Med Chem 2005;48:4558-4575.
39. Aqvist J, Luzhkov VB, Brandsdal BO. Ligand binding affinities from MD simulations. Acc Chem Res 2002;35:358-365.
40. Kalra P, Reddy TV, Jayaram B. Free energy component analysis for drug design: a case study of HIV-I protease inhibitor binding. J Med Chem 2001;44:4325-4338.
41. Brooijmans N, Kuntz ID. Molecular recognition and docking algorithms. Ann Rev Biophys Biomol Struct 2003;32:335-373.
42. Wang R, Lu Y, Wang S. Comparitive evaluation of 11 scoring functions for molecular docking. J Med Chem 2003;46:2287-2303.
43. Ferrara P, Gohlke H, Price DJ, Klebe G, Brooks CL, III. Assessing scoring functions for protein-ligand interactions. J Med Chem 2004;47:3032-3047.
44. Perola E, Walters PW, Charifson PS. A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance. Proteins: Struct Funct Genet 2004;56:235-249.
45. Donini OAT, Kollman PA. Calculation and prediction of binding free energies for matrix metalloproteinases. J Med Chem 2000; 43:4180-4188.
46. Raha K, Merz KM, Jr. A quantum mechanics based scoring function: study of zinc ion-mediated ligand binding. J Am Chem Soc 2004;126:1020-1021.
47. Toba S, Damodaran KV, Merz KM, Jr. Binding preferences of hydroxamate inhibitors of the matrix metalloproteinase human fibroblast collagenase. J Med Chem 1999;42:1225-1234.
48. Hou T, Zhang W, Xu XJ. Binding affinities for a series of selective inhibitors of gelatinase-A using molecular dynamics with a linear interaction energy approach. J Phys Chem B 2001;105: 5304-5315.
49. Hu X, Shelver WH. Docking studies of matrix metalloproteinase inhibitors: zinc parameter optimization to improve the binding free energy prediction. J Mol Graph Model 2003;22: 115-126.
50. Rizzo RC, Toba S, Kuntz ID. A molecular basis for the selectivity of thiadiazole urea inhibitors with stromelysin-1 and gelatinase-A from generalized born molecular dynamics simulations. J Med Chem 2004;47:3065-3074.
51. Khandelwal A, Lukacova V, Comez D, Kroll DM, Raha S, Balaz S. A combination of docking, QM/MM methods, and MD simulation for binding affinity estimation of metalloprotein ligands. J Med Chem 2005;48:5437-5447.
52. Hu X, Balaz S, Shelver WH. A practical approach to docking of zinc metalloproteinase inhibitors. J Mol Graph Model 2004;22: 293-307.
53. Jain T, Jayaram B. An all atom energy based computational protocol for predicting binding affinities of protein-ligand complexes. FEBS Lett 2005;579:6659-6666.
54. Arora N, Jayaram B. Energetics of base pairs in B-DNA in solution: an appraisal of potential functions and dielectric treatments. J Phys Chem 1998;102:6139-6144.
55. Eisenberg D, McLachlan AD. Solvation energy in protein folding and binding. Nature 1986;319:199-203.
56. Cornell WD, Cieplak P, Bayly CI, Gould IR, Merz KM, et al. A second generation force field for the simulation of proteins, nucleic acids and organic molecules. J Am Chem Soc 1995;117: 5179-5197.
57. Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA. Development and testing of a general AMBER force field. J Comput Chem 2004;25:1157-1174.
58. Rashin AA, Honig B. Reevaluation of the Born model of ion hydration. J Phys Chem 1985;89:5588-5593.
59. Lee KH, Xie D, Freire E, Amzel LM. Estimation of changes in side chain configurational entropy in binding and folding: general methods and application to helix formation. Proteins: Struct Funct Genet 1994;20:68-84.
60. Pickett SD, Sternberg MJE. Empirical scale of side-chain conformational entropy in protein folding. J Mol Biol 1993;231:825-839.
61. Berman HM, et al. The protein data bank. Nucleic Acids Res 2000;28:235-242.
62. Roche O, Kiyama R, Brooks CL, III. Ligand-protein database: linking protein-ligand complex structures to binding data. J Med Chem 2001;44:3592-3598.
63. Puvanendrampillai D, Mitchell JBO. Protein ligand database (PLD): additional understanding of the nature and specificity of protein-ligand complexes. Bioinformatics 2003;19:1856-1857.
64. Block P, Sotriffer CA, Dramburg I, Klebe G, Affin DB. A freely accessible database of affinities of protein-ligand complexes from the PDB. Nucleic Acids Res 2006;34:D522-D526.
65. Wang R, Fang X, Lu Y, Yang CY, Wang S. The PDBbind database: methodologies and updates. J Med Chem 2005;48:4111-4119.
66. Schmidt MW, Baldridge KK, Boatz JA, Elbert ST, Gordon MS, et al. General atomic and molecular electronic structure system. J Comput Chem 1993;14:1347-1363.
67. Wang J, Wang W, Kollman PA, Case DA. Automatic atom type and bond type perception in molecular mechanical calculations. J Mol Graph Model 2006;25:247-260.
68. Pearlman DA, Case DA, Caldwell JW, Ross WS, Cheathem JE, III, et al. AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Comput Phys Commun 1995;91:1-41.
69. Wallace AC, Laskowski RA, Thornton JM. LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions. Prot Eng 1995;8:127-134.
70. 2! J Mol Graph Model 2002;20:269-276.
71. Golbraikh A, Shen M, Xiao Z, Xiao YD, Lee KH, Tropsha A. Rational selection of training and test sets for the development of validated QSAR models. J Comput-Aided Mol Des 2003;17:241-253.