HarmonyDOCK: The structural analysis of poses in protein-ligand docking

Journal of Computational Biology

Volumn 21, Issue 3, 2014, Pages 247-256

  Plewczynski, Dariusz ^a   Philips, Anna ^b   Grotthuss, Marcin Von ^c   Rychlewski, Leszek ^c   Ginalski, Krzysztof ^a  

^a UNIVERSITY OF WARSAW   (Poland)

^b ADAM MICKIEWICZ UNIVERSITY   (Poland)

^c BioInfoBank Institute   (Poland)

Author keywords

computational molecular biology; machine learning; protein motifs; protein structure

Indexed keywords

LIGAND; PROTEIN;

ARTICLE; BINDING SITE; CHEMISTRY; COMPUTER PROGRAM; DRUG DESIGN; MOLECULAR DOCKING; PROTEIN BINDING; PROTEIN CONFORMATION;

BINDING SITES; DRUG DESIGN; LIGANDS; MOLECULAR DOCKING SIMULATION; PROTEIN BINDING; PROTEIN CONFORMATION; PROTEINS; SOFTWARE;

EID: 84896753876     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/cmb.2009.0111     Document Type: Article

References (17)

1. Block, P., Sotriffer, C.A., et al. 2006. AffinDB: a freely accessible database of affinities for protein-ligand complexes from the PDB. Nucleic Acids Res. 34, D522-D526.
2. Bohm, H.J. 1992a. The computer program LUDI: a new method for the de novo design of enzyme inhibitors. J. Comput. Aided Mol. Design 6, 61-78.
3. Bohm, H.J. 1992b. LUDI: rule-based automatic design of new substituents for enzyme inhibitor leads. J. Comput. Aided. Mol. Design 6, 593-606.
4. Bohm, H.J. 1994. On the use of LUDI to search the Fine Chemicals Directory for ligands of proteins of known three-dimensional structure. J. Comput. Aided Mol. Design 8, 623-32.
5. Bohm, H.J., Boehringer, M., et al. 2000. Novel inhibitors of DNA gyrase: 3D structure based biased needle screening, hit validation by biophysical methods, and 3D guided optimization. A promising alternative to random screening. J. Med. Chem. 43, 2664-2675.
6. Eldridge, M.D., Murray, C.W., et al. 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. Design 11, 425-45. (Pubitemid 127505895)
7. Gohlke, H., Hendlich, M., et al. 2000. Knowledge-based scoring function to predict protein-ligand interactions. J. Mol. Biol. 295, 337-356. (Pubitemid 30045364)
8. Goss, K.U., and Schwarzenbach, R.P. 2003. Rules of thumb for assessing equilibrium partitioning of organic compounds: Successes and pitfalls. J. Chem. Educ. 80, 450-455.
9. Jorgensen, W.L., and Tirado-Rives, J. 2005. Molecular modeling of organic and biomolecular systems using BOSS and MCPRO. J. Comput. Chem. 26, 1689-1700. (Pubitemid 43076181)
10. Katchalski-Katzir, E., Shariv, I., et al. 1992. Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques. Proc. Natl. Acad. Sci. USA 89, 2195-2199.
11. Lodish, H., Berk, A., et al. 2000. Chemical foundations. Covalent bounds and noncovalent interactions, 31-39. In Lodish, H., Berk, A., Zipurskyet, L., et al., eds. Molecular Cell Biology, 4th ed. W.H. Freeman, New York.
12. Meng, E.C., Shoichet, B.K., et al. 1992. Automated docking with grid-based energy evaluation. J. Comput. Chem. 13, 505-524.
13. Mitchell, T. 1997. Genetic algorithms, 249-270. In Mitchell, T., ed. Machine Learning. McGraw Hill, New York.
14. Ritchie, D.W., and Kemp, G.J. 2000. Protein docking using spherical polar Fourier correlations. Proteins 39, 178-194. (Pubitemid 30176485)
15. Rodwell, V.W. 1999. Water and pH, 28-37. In Murray, R.K., Granner, D.K., and Rodwell, V.W., eds. Harper's Biochemistry. Appleton & Lange, New York.
16. Terfloth, L. 2003. Drug design, 597-618. In Gasteiger, J., and Engel, T., eds. Chemoinformatics: A Textbook. Wiley, New York.
17. Wermuth, C. 2003. Strategies in the search for new lead compounds or original working hypotheses, 69-88. In Wermuth, C.G., ed. The Practice of Medicinal Chemistry, 2nd ed. Academic Press, London.