FReDD: Supporting mining strategies through a flexible-receptor docking database

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5676 LNBI, Issue , 2009, Pages 143-146

  Winck, Ana T ^a   MacHado, Karina S ^a   Norberto De Souza, Osmar ^a   Ruiz, Duncan D D ^a  

^a PONTIFICAL CATHOLIC UNIVERSITY OF RIO GRANDE DO SUL   (Brazil)

Author keywords

Data mining; Data preparation; Database; Molecular docking

Indexed keywords

DATA PREPARATION; DATABASE; LIGAND DOCKING; MOLECULAR DOCKING; MOLECULAR DYNAMICS SIMULATIONS; MYCOBACTERIUM TUBERCULOSIS; RECEPTOR FLEXIBILITY;

BIOLOGY; DATABASE SYSTEMS; DOCKING; LIGANDS; MOLECULAR DYNAMICS; MOLECULAR MODELING; STRATEGIC PLANNING;

BIOINFORMATICS;

EID: 69949120570     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-03223-3_13     Document Type: Conference Paper

References (16)

1. Drews, J.: Drug discovery: A historical perspective computational methods for biomolecular docking. Current Opinion in Structural Biology 6, 402-406 (1996)
2. Kuntz, I.D.: Structure-based strategies for drug design and discovery. Science 257, 1078-1082 (1992)
3. Lybrand, T.P.: Ligand-protein docking and rational drug design. Current Opinion in Structural Biology 5, 224-228 (1995)
4. Totrov, M., Abagyan, R.: Flexible ligand docking to multiple receptor conformations: a pratical alternative. Current Opinion in Structural Biology 18, 178-184 (2008)
5. Cozzini, P., et al.: Target Flexibility: An Emerging Consideration in Drug Discovery and Design. Journal of Medicinal Chemistry 51, 6237-6255 (2008)
6. Alonso, H., et al.: Combining Docking and Molecular Dynamic Simulations in Drug Design. Med. Res. Rev. 26, 531-568 (2006)
7. van Gunsteren, W.F., Berendsen, H.J.C.: Computer Simulation of Molecular Dynamics Methodology, Applications and Perspectives in Chemistry. Angew. Chem. Int. Ed. Engl. 29, 992-1023 (1990)
8. Dessen, A., et al.: Crystal structure and function of the isoniazid target of Mycobacterium tuberculosis. Science 267, 1638-1641 (1995)
9. Pearlman, D.A., et al.: AMBER, a computer program for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to elucidate the structures and energies of molecules. Comp. Phys. Commun. 91, 1-41 (1995)
10. Schroeder, E.K., et al.: Molecular Dynamics Simulation Studies of the Wild-Type, I21V, and I16T Mutants of Isoniazid-Resistant Mycobacterium tuberculosis Enoyl Reductase (InhA) in Complex with NADH: Toward the Understanding of NADH-InhA Different Affinities. Biophysical Journal 89, 876-884 (2005)
11. Kuo, M.R., et al.: Targeting tuberculosis and malaria through inhibition of enoyl reductase: compound activity and structural data. J. Biol. Chem. 278, 20851-20859 (2003)
12. Oliveira, J.S., et al.: An inorganic iron complex that inhibits wild-type and an isoniazid-resistant mutant 2-trans-enoyl-ACP (CoA) reductase from Mycobacterium tuberculosis. Chem. Comm. 3, 312-313 (2004)
13. Machado, K.S., et al.: Automating Molecular Docking with Explicit Receptor Flexibility Using Scientific Workflows. In: Sagot, M.-F., Walter, M.E.M.T. (eds.) BSB 2007. LNCS (LNBI), vol. 4643, pp. 1-11. Springer, Heidelberg (2007)
14. Morris, G.M., et al.: Automated Docking Using a Lamarckian Genetic Algorithm and Empirical Binding Free Energy Function. J. Comput. Chemistry 19, 1639-1662 (1998)
15. Machado, K.S., et al.: Extracting Information from Flexible Receptor-Flexible Ligand Docking Experiments. In: Bazzan, A.L.C., Craven, M., Martins, N.F. (eds.) BSB 2008. LNCS (LNBI), vol. 5167, pp. 104-114. Springer, Heidelberg (2008)
16. Waikato Environment for Knowledge, Analysis, http://www.cs.waikato.ac.nz/ ml/weka