BioDrugScreen: A computational drug design resource for ranking molecules docked to the human proteome

Nucleic Acids Research

Volumn 38, Issue SUPPL.1, 2009, Pages

  Li, Liwei ^a   Bum Erdene, Khuchtumur ^a   Baenziger, Peter H ^a   Rosen, Joshua J ^b   Hemmert, Jamison R ^a   Nellis, Joy A ^a   Pierce, Marlon E ^b   Meroueh, Samy O ^a  

^a INDIANA UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b INDIANA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEOME; DRUG; LIGAND;

ACCESS TO INFORMATION; ARTICLE; BIODRUGSCREEN; COMPUTER INTERFACE; CRYSTAL STRUCTURE; DRUG DESIGN; DRUG IDENTIFICATION; DRUG RESEARCH; DRUG SCREENING; DRUG TARGETING; HUMAN; MOLECULAR DOCKING; PRIORITY JOURNAL; PROTEIN STRUCTURE; PROTEOMICS; REFERENCE DATABASE; SCORING SYSTEM; THREE DIMENSIONAL IMAGING; BIOLOGY; CHEMISTRY; COMPUTER PROGRAM; GENETIC DATABASE; INFORMATION RETRIEVAL; INSTRUMENTATION; INTERNET; METHODOLOGY; NUCLEIC ACID DATABASE; PROTEIN BINDING;

COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; DATABASES, NUCLEIC ACID; DRUG DESIGN; DRUG EVALUATION, PRECLINICAL; HUMANS; INFORMATION STORAGE AND RETRIEVAL; INTERNET; LIGANDS; PHARMACEUTICAL PREPARATIONS; PROTEIN BINDING; PROTEOME; PROTEOMICS; SOFTWARE;

EID: 75549084941     PISSN: 03051048     EISSN: 13624962     Source Type: Journal    
DOI: 10.1093/nar/gkp852     Document Type: Article

References (47)

1. Shoichet, B.K. (2004) Virtual screening of chemical libraries. Nature, 432, 862-865.
2. Song, H., Wang, R., Wang, S. and Lin, J. (2005) A low-molecular-weight compound discovered through virtual database screening inhibits Stat3 function in breast cancer cells. Proc. Natl Acad. Sci. USA, 102, 4700-4705.
3. Bowman, A.L., Nikolovska-Coleska, Z., Zhong, H., Wang, S. and Carlson, H.A. (2007) Small molecule inhibitors of the MDM2-p53 interaction discovered by ensemble-based receptor models. J. Am. Chem. Soc., 129, 12809-12814.
4. Betzi, S., Restouin, A., Opi, S., Arold, S.T., Parrot, I., Guerlesquin, F., Morelli, X. and Collette, Y. (2007) Protein protein interaction inhibition (2P2I) combining high throughput and virtual screening: application to the HIV-1 Nef protein. Proc. Natl Acad. Sci. USA, 104, 19256-19261.
5. Kitchen, D.B., Decornez, H., Furr, J.R. and Bajorath, J. (2004) Docking and scoring in virtual screening for drug discovery: methods and applications. Nat. Rev., 3, 935-949.
6. Dias, R. and de Azevedo, W.F. (2008) Molecular docking algorithms. Curr. Drug Targets, 9, 1040-1047.
7. Meng, E.C., Shoichet, B.K. and Kuntz, I.D. (1992) Automated docking with grid-based energy evaluation. J. Comput. Chem., 13, 505-524.
8. Morris, G.M., Goodsell, D.S., Halliday, R.S., Huey, R., Hart, W.E., Belew, R.K. and Olson, A.J. (1998) Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J. Comput. Chem., 19, 1639-1662.
9. Berendsen, H.J.C., Vanderspoel, D. and Vandrunen, R. (1995) Gromacs - a message-passing parallel molecular-dynamics implementation. Comput. Phys. Commun., 91, 43-56.
10. Rarey, M., Kramer, B., Lengauer, T. and Klebe, G. (1996) A fast flexible docking method using an incremental construction algorithm. J. Mol. Biol., 261, 470-489.
11. 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. et al. (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J. Med. Chem., 47, 1739-1749.
12. Bohm, H.J. (1994) The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure. J. Comput. Aided Mol. Des., 8, 243-256.
13. Eldridge, M.D., Murray, C.W., Auton, T.R., Paolini, G.V. and Mee, R.P. (1997) 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., 11, 425-445.
14. Bohm, H.J. (1998) Prediction of binding constants of protein ligands: a fast method for the prioritization of hits obtained from de novo design or 3D database search programs. J. Comput. Aided Mol. Des., 12, 309-323.
15. Muegge, I. and Martin, Y.C. (1999) A general and fast scoring function for protein-ligand interactions: a simplified potential approach. J. Med. Chem., 42, 791-804.
16. Muegge, I. (2006) PMF scoring revisited. J. Med. Chem., 49, 5895-5902.
17. Gohlke, H., Hendlich, M. and Klebe, G. (2000) Knowledge-based scoring function to predict protein-ligand interactions. J. Mol. Biol., 295, 337-356.
18. Velec, H.F., Gohlke, H. and Klebe, G. (2005) 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., 48, 6296-6303.
19. Huey, R., Morris, G.M., Olson, A.J. and Goodsell, D.S. (2007) A semiempirical free energy force field with charge-based desolvation. J. Comput. Chem., 28, 1145-1152.
20. Jones, G., Willett, P. and Glen, R.C. (1995) A genetic algorithm for flexible molecular overlay and pharmacophore elucidation. J. Comput. Aided Mol. Des., 9, 532-549.
21. Jones, G., Willett, P., Glen, R.C., Leach, A.R. and Taylor, R. (1997) Development and validation of a genetic algorithm for flexible docking. J. Mol. Biol., 267, 727-748.
22. Schneidman-Duhovny, D., Dror, O., Inbar, Y., Nussinov, R. and Wolfson, H.J. (2008) PharmaGist: a webserver for ligand-based pharmacophore detection. Nucleic Acids Res., 36, W223-W228.
23. Huang, Y.J., Hang, D., Lu, L.J., Tong, L., Gerstein, M.B. and Montelione, G.T. (2008) Targeting the human cancer pathway protein interaction network by structural genomics. Mol. Cell. Proteomics, 7, 2048-2060.
24. Wishart, D.S., Knox, C., Guo, A.C., Cheng, D., Shrivastava, S., Tzur, D., Gautam, B. and Hassanali, M. (2008) DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res., 36, D901-D906.
25. Wishart, D.S., Knox, C., Guo, A.C., Shrivastava, S., Hassanali, M., Stothard, P., Chang, Z. and Woolsey, J. (2006) DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res., 34, D668-D672.
26. Hendlich, M., Bergner, A., Gunther, J. and Klebe, G. (2003) Relibase: design and development of a database for comprehensive analysis of protein-ligand interactions. J. Mol. Biol., 326, 607-620.
27. Word, J.M., Lovell, S.C., Richardson, J.S. and Richardson, D.C. (1999) Asparagine and glutamine: using hydrogen atom contacts in the choice of side-chain amide orientation. J. Mol. Biol., 285, 1735-1747.
28. Sanner, M.F. (1999) Python: a programming language for software integration and development. J. Mol. Graphics Mod., 17, 57-61.
29. Irwin, J.J. and Shoichet, B.K. (2005) ZINC-a free database of commercially available compounds for virtual screening. J. Chem. Inf. Model, 45, 177-182.
30. Zhang, C., Liu, S., Zhu, Q. and Zhou, Y. (2005) A knowledge-based energy function for protein-ligand, protein-protein, and protein-DNA complexes. J. Med. Chem., 48, 2325-2335.
31. Wang, R., Lai, L. and Wang, S. (2002) Further development and validation of empirical scoring functions for structure-based binding affinity prediction. J. Comput. Aided Mol. Des., 16, 11-26.
32. Case, D.A., Cheatham, T., Darden, T., Gohlke, H., Luo, R., Merz, K.M. Jr, Onufriev, A., Simmerling, C., Wang, B. and Woods, R. (2005) The Amber biomolecular simulation programs. J. Comput. Chem., 26, 1668-1688.
33. Li, L., Uversky, V.N., Dunker, A.K. and Meroueh, S.O. (2007) A computational investigation of allostery in the catabolite activator protein. J. Am. Chem. Soc., 129, 15668-15676.
34. Jakalian, A., Bush, B.L., Jack, D.B. and Bayly, C.I. (2000) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: I. Method. J. Comput. Chem., 21, 132-146.
35. Jakalian, A., Jack, D.B. and Bayly, C.I. (2002) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J. Comput. Chem., 23, 1623-1641.
36. Fogolari, F., Brigo, A. and Molinari, H. (2002) The Poisson-Boltzmann equation for biomolecular electrostatics: a tool for structural biology. J. Mol. Recognit., 15, 377-392.
37. Still, W.C., Tempczyk, A., Hawley, R.C. and Hendrickson, T. (1990) Semianalytical treatment of solvation for molecular mechanics and dynamics. J. Am. Chem. Soc., 112, 6127-6129.
38. Wishart, D.S., Knox, C., Guo, A.C., Cheng, D., Shrivastava, S., Tzur, D., Gautam, B. and Hassanali, M. (2008) DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res., 36, D901-D906.
39. Li, L. and Meroueh, S.O. (2008) Encyclopedia for the Life Sciences. John Wiley and Sons, London.
40. Liang, S., Li, L., Hsu, W.L., Pilcher, M.N., Uversky, V., Zhou, Y., Dunker, A.K. and Meroueh, S.O. (2009) Exploring the molecular design of protein interaction sites with molecular dynamics simulations and free energy calculations. Biochemistry, 48, 399-414.
41. Li, L., Liang, S., Pilcher, M.M. and Meroueh, S.O. (2009) Incorporating receptor flexibility in the molecular design of protein interfaces. Protein Eng. Des. Sel., 22, 575-586.
42. Kuhn, D., Weskamp, N., Schmitt, S., Hullermeier, E. and Klebe, G. (2006) From the similarity analysis of protein cavities to the functional classification of protein families using Cavbase. J. Mol. Biol., 359, 1023-1044.
43. Kuhn, D., Weskamp, N., Hullermeier, E. and Klebe, G. (2007) Functional classification of protein kinase binding sites using cavbase. ChemMedChem, 2, 1432-1447.
44. Huang, B.D. and Schroeder, M. (2006) LIGSITE(csc): predicting ligand binding sites using the Connolly surface and degree of conservation. BMC Struct. Biol., 6, 19.
45. Morris, G.M., Huey, R. and Olson, A.J. (2008) Using AutoDock for ligand-receptor docking. Curr. Protoc. Bioinformatics, Chapter 8, Unit 8.14.
46. Irwin, J.J. and Shoichet, B.K. (2005) ZINC-a free database of commercially available compounds for virtual screening. J. Chem. Inf. Model, 45, 177-182.
47. Wang, Y.L., Xiao, J.W., Suzek, T.O., Zhang, J., Wang, J.Y. and Bryant, S.H. (2009) PubChem: a public information system for analyzing bioactivities of small molecules. Nucleic Acids Res., 37, W623-W633.