Importance of molecular computer modeling in anticancer drug development

Journal of B.U.ON.

Volumn 12, Issue SUPPL. 1, 2007, Pages

  Geromichalos, George D ^a  

^a THEAGENIO CANCER HOSPITAL   (Greece)

Author keywords

Computational molecular docking; Computer aided molecular design (CAMD); Drug discovery and development; Mechanism of action; Molecular modeling; Virtual high throughput screening (VHTS)

Indexed keywords

ANTIBIOTIC AGENT; ANTINEOPLASTIC AGENT; BCR ABL PROTEIN; DACTINOMYCIN; DORZOLAMIDE; ENZYME INHIBITOR; G PROTEIN COUPLED RECEPTOR; GEFITINIB; GENISTEIN; IMATINIB; MITOXANTRONE; OLOMOUCINE; PROTEIN KINASE; STAUROSPORINE;

ACUTE LYMPHOCYTIC LEUKEMIA; ALGORITHM; ANTINEOPLASTIC ACTIVITY; BIOINFORMATICS; CHRONIC MYELOID LEUKEMIA; COMPUTER AIDED DESIGN; COMPUTER MODEL; CONFERENCE PAPER; CRYSTALLOGRAPHY; DATA MINING; DRUG ACTIVITY; DRUG BINDING SITE; DRUG DESIGN; DRUG EFFICACY; DRUG MECHANISM; DRUG SCREENING; DRUG SOLUBILITY; DRUG SPECIFICITY; DRUG STRUCTURE; DRUG TARGETING; ENZYME INHIBITION; HIGH THROUGHPUT SCREENING; HUMAN; MOLECULAR DOCKING; MOLECULAR DYNAMICS; MOLECULAR MODEL; MOLECULAR WEIGHT; NONHUMAN; PROTEIN DATABASE; PROTEIN PROTEIN INTERACTION; QUANTITATIVE STRUCTURE ACTIVITY RELATION; SCORING SYSTEM;

ALGORITHMS; ANIMALS; ANTINEOPLASTIC AGENTS; BINDING SITES; COMPUTATIONAL BIOLOGY; COMPUTER-AIDED DESIGN; CRYSTALLOGRAPHY; DATABASES, GENETIC; DRUG DESIGN; HISTORY, 20TH CENTURY; HISTORY, 21ST CENTURY; HUMANS; LIGANDS; MODELS, MOLECULAR; MOLECULAR STRUCTURE; NUCLEIC ACID CONFORMATION; NUCLEIC ACIDS; PROTEIN BINDING; PROTEIN CONFORMATION; PROTEINS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 36749044271     PISSN: 11070625     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (39)

1. Ohlstein EH, Ruffolo RR Jr, Elliott JD. Drug discovery in the next millennium. Annu Rev Pharmacol Toxicol 2000; 40: 177-191.
2. Cunnigham MJ. Genomics and proteomics. The new millennium of drug discovery and development. J Pharmacol Toxicol Meth 2000; 44: 291-300.
3. Debouck C, Metcalf B. The impact of genomics on drug discovery. Annu Rev Pharmacol Toxicol 2000; 40: 193-207.
4. Li Q, XuW. Curr Med Chem -Anti-Cancer Agents 2005; 5: 53-63.
5. Tomich CH, Silva CHTP, Carvalho I. Homology modeling and molecular interaction field studies of a-glycosidase as a guide to structure-based design of novel proposed anti-HIV inhibitors. J Comput-Aided Mot Design 2005; 19: 83-92.
6. Zubrod CG. Origins and development of chemotherapy research at the National Cancer Institute. Cancer Treat Rep 1984; 68: 9-19.
7. Skipper HE, Schabet FM Jr, Wilcox WS. Experimental evaluation of potential anticancer agents. XII. On the criteria and kinetics associated with "curability" of experimental leukemia. Cancer Chemother Rep 1964; 35: 1 -111.
8. Monks A, Scudiero DA, Johnson GS, Paull KD, Sausville EA. The NCI anti-cancer drug screen: a smart screen to identify effectors of novel targets. Anticancer Drug Des 1997; 12: 533-541.
9. Scherf U, Ross DT, Waltham M et al. A gene expression database for the molecular pharmacology of cancer. Nat Genet 2000; 24: 236-244.
10. Shayne Cox Gad (Ed). Drug Discovery Handbook. Wiley-Interscience, 2005.
11. Madsen U (Ed). Textbook of Drug Design and Discovery. CRC, 2002.
12. Greer J, Erickson JW, Baldwin JJ, Varney MD. Application ofthe three-dimensional structures ofprotein target molecules in structure-based drug design. J Med Chem 1994; 37: 1035-1054.
13. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Del Rev 2001; 46: 3-26.
14. Deininger MW, Goldman JM, Lydon N, Melo JV. The tyrosine kinase inhibitor CGP57148B selectively inhibits the growth of BCR-ABL-positive cells. Blood 1997; 90: 3691-3698.
15. Gibbs JB, Oliff A. The potential of famesyltransferase inhibitors as cancer chemotherapeutics. Annu Rev Pharmacol Toxicol 1997; 37: 143-166.
16. Barker AJ, Gibson KH, Grundy W et al. Studies leading to the identification of ZD1839 (IRESSA): an orally active, selective epidermal growth factor receptor tyrosine kinase inhibitor targeted to the treatment of cancer. Bioorg Med Chem Lett 2001; 11: 1911-1914.
17. Strausberg RL. The Cancer Genome Anatomy Project: new resources for reading the molecular signatures of cancer. J Pathol 2001; 195: 31-40.
18. Burbaum JJ, Sigal NH. New technologies for high-throughput screening. Curr Opin Chem Biol 1997; 1: 72-78.
19. Liu B, Li S, Hu J. Technological advances in high-throughput screening. Am J Pharmacogenomics 2004; 4: 263-276.
20. Roche O, Kiyama R, Brooks CL. 3rd Ligand-protein database: linking protein-ligand complex structures to binding data. J Med Chem 2001; 44: 3592-3598.
21. Chen YZ, Zhi DG. Ligand-protein inverse docking and its potential use in the computer search of protein targets of a small molecule. Proteins 2001; 43: 217-226.
22. Lamb ML, Burdick KW, Toba S et al. Design, docking, and evaluation of multiple libraries against multiple targets. Proteins 2001; 42: 296-318.
23. Patani GA, LaVoie EJ. Bioisosterism: A Rational Approach in Drug Design. Chem Rev 1996; 96: 3147-3176.
24. Bonchev DH. Rouvray: Chemical Graph Theory: Introduction and Fundamentals. Gordon and Breach Science Publishers, New York, NY, USA, 1990.
25. Leach A (Ed). Molecular Modelling: Principles and Applications. Prentice Hall, Upper Saddle River, NJ, USA, 2001.
26. Schölkopf B, Tsuda K, Vert JP (Eds). Kernel Methods in Computational Biology. MIT Press, Cambridge, MA, 2004.
27. Gusfield D (Ed). Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology. Cambridge University Press, UK, 1997.
28. Freyhult EK, Andersson K, Gustafsson MG. Structural modeling extends QSAR analysis of antibody-lysozyme interactions to 3D-QSAR. J Biophys 2003; 84: 25-31.
29. Todeschini R, Consonni V (Eds). Handbook of Molecular Descriptors. Wiley-VCH, Verlag GmbH & Co. KGaA, Weinheim, Germany, 2000.
30. Duda RO, Hart PE, Stork DG. Pattern Classification. John Wiley & Sons, Sussek, England, 2001.
31. Wildman SA, Crippen GM. Prediction of Physicochemical Parameters by Atomic Contributions. J Chem Inf Comput Sci 1999; 39: 868-873.
32. Roychoudhury S, Blondelle SE, Collins SM et al. Use of combinatorial library screening to identify inhibitors of a bacterial two-component signal transduction kinase. Mol Divers 1998; 4: 173-182.
33. Joseph-McCarthy D. Computational approaches to structure-based ligand design. Pharmacol Ther 1999; 84: 179-191.
34. Krstenansky JL, Khmelnitsky Y. Biocatalytic combinatorial synthesis. Bioorg Med Chem 1999; 7: 2157-2162.
35. Hunter WN. Rational drug design: a multidisciplinary approach. Mol Med Today 1995; 1: 31-34.
36. Drews J. Drug discovery: a historical perspective. Science 2000; 287: 1960-1964.
37. Liggett SB. Pharmacogenetic applications of the Human Genome project. Nat Med 2001; 7: 281-283.
38. Buchdunger E, Zimmermann J, Mett H et al. Inhibition of the AbI protein-tyrosine kinase in vitro and in vivo by a 2-phenytaminopyrimidine derivative. Cancer Res 1996; 56: 100-104.
39. Neamati N, Barchi JJ Jr. New Paradigms in Drug Design and Discovery. Chemistry 2002; 2: 211-227.