A KDD approach for designing filtering strategies to improve virtual screening

KDIR 2009 - 1st International Conference on Knowledge Discovery and Information Retrieval, Proceedings

Volumn , Issue , 2009, Pages 146-151

  Ghemtio, Leo ^a   Smaïl Tabbone, Malika ^a   Devignes, Marie Dominique ^a   Souchet, Michel ^a   Maigret, Bernard ^a  

^a LORIA   (France)

Author keywords

3D structure; Data mining; Data retrieval; Heterogeneous data integration; KDD; Protein ligand interaction; Virtual screening

Indexed keywords

3D STRUCTURE; DATA RETRIEVAL; HETEROGENEOUS DATA; PROTEIN-LIGAND INTERACTIONS; VIRTUAL SCREENING;

CHEMICAL COMPOUNDS; DATA HANDLING; DATA MINING; FILTRATION; INFORMATION RETRIEVAL; LIBRARIES; PROTEINS; TARGETS; THREE DIMENSIONAL;

LIGANDS;

EID: 77955399283     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. Beautrait, A. et al. 2008. Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment, Journal of Molecular Modeling, 14, 135-48.
2. Bennett, D.J., Carswell, E.L., Cooke, A.J., Edwards, A.S. & Nimz, O. 2008. Design, structure activity relationships and X-Ray co-crystallography of non-steroidal LXR agonists. Curr Med Chem 15, 195-209. (Pubitemid 351234623)
3. Berman, H., WestBrook, J., Feng, A., Gililand, G., Bhat, T., Weissig, H., Shinlyalov, I., Bourne, P., 2000. The Protein Data Bank. Nucl. Acid. Res. 28: 235-242.
4. Cai, W., Xu J., Shao X., Leroux V., Beautrait A., Maigret B., 2008. SHEF: a vHTS geometrical filter using coefficients of spherical harmonic molecular surfaces. J Mol Model 14, 393-401.
5. Dzeroski, S., and Lavrac, N.(Eds.), 2001. Relational Data Mining. Springer.
6. Fayyad, U., Piatetsky-Shapiro, G., Smyth, P., 1996. From Data Mining to Knowledge Discovery: an Overview. MIT Press, Cambridge MA.
7. Feher, M. (2006) Consensus scoring for protein-ligand interactions, Drug Discovery Today, 11, 421-428.
8. Finn, P., Muggleton, S., Page, D., Srinivasan, A., 1998. Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL. Machine Learning 30(2-3): 241-270. (Pubitemid 128631745)
9. Halgren, T. A., Murphy, R. B., Friesner, R. A., Beard, H. S., Frye, L. L., Pollard, W. T., Banks, J. L. 2004. Glide: A New Approach for Rapid, Accurate Docking and Scoring. J. Med. Chem., 47, 1750-1759.
10. Janowski, B.A. et al. 1999. Structural requirements of ligands for the oxysterol liver X receptors LXRalpha and LXRbeta. Proc Natl Acad Sci U S A 96, 266-71.
11. Jones G., Willett P., Glen R.C., Leach A.R., Taylor R. 1997. Development and validation of a genetic algorithm for flexible docking. J Mol Biol., 267, 727-48.
12. Jorgensen, W. L., 2004. The Many Roles of Computation in Drug Discovery. Science 303, 5665-5682.
13. Karp P., Lee T., Wagner V., 2008. BioWarehouse: Relational Integration of Eleven Bioinformatics Databases and Formats. In Data Integration in the Life Sciences, LNCS 5109, Springer Berlin / Heidelberg.
14. Kirchmair, J., Distinto, S., Schuster, D., Spitzer, G., Langer, T. and Wolber, G. (2008) Enhancing drug discovery through in silico screening: strategies to increase true positives retrieval rates, Current medicinal chemistry, 15, 2040-2053.
15. Köppen, H., 2009. Virtual screening - What does it give us? Curr Opin Drug Discov Devel., 12(3), 397-407.
16. Krovat, E.M., Steindl T., Langer, T., 2005. Recent Advances in Docking and Scoring, Current Computer - Aided Drug Design, 1, 93-102.
17. Lala, D.S. 2005. The liver X receptors. Curr Opin Investig Drugs 6, 934-43.
18. Maron, O., T. Lozano-Perez, T., 1998. A framework for multiple-instance learning. In Advances in Neural Information Processing Systems (NIPS), pages 570-576. MIT Press.
19. Page, D., Craven, M., 2003. Biological applications of multi-relational data mining. SIGKDD Explorations 5(1): 69-79.
20. Spencer, T.A. et al. 2001. Pharmacophore analysis of the nuclear oxysterol receptor LXRalpha. J Med Chem 44, 886-97.
21. Winkler D.A., 2002. The role of quantitative structure-activity relationships in molecular discovery. Briefings in Bioinformatics 3, 73-86
22. Witten, I., and Frank, E., 2005. Data Mining: Practical Machine Learning Tools and Techniques (Second Edition), Morgan Kaufmann.