|Dr. Iwona E. Weidlich|| at 11:00
Location: 38A/5th floor conference room
Affiliation: Computational Drug Design Systems (CODDES), LLC
Host: Evan Bolton
PubChem Bioassay Data - Key source for SAR Models with Advanced Machine Learning Methods in Drug Repurposing
Developing new drug candidates has turned into a billion-dollar expense that is not delivering enough profitable products to market. Therefore, there is a rising interest in using bioactivity data in repositioning existing drugs for new medical indications.
A large set of small molecules with measured bioactivity data has been compiled by Chemical Biology Lab CADD group from the data available from PubChem.1-5 We implemented two SAR models using modern machine learning classifiers Random Forest and k Nearest Neighbor Simulated Annealing for 679 small molecules with measured inhibition activity for NS5B genotype 1b. Most of the data used for the SAR training was collected by the Molecular Libraries Program.
We developed SAR models for HCV RNA Polymerase.6 Our models revealed new indication for a known hypertension therapeutic. Application of these SAR models to screen drug-like databases, cross-docking and computational drug repositioning methods will be presented.
2 Q.Li, Y.Wang, S.H.Bryant, A novel method for mining highly imbalanced high-throughput screening data in PubChem, Bioinformatics, 25 (24), 2009, 3310-3316.
3 Xiang-Qun Xie, Jian-Zhong Chen, Data mining a small molecule drug screening representative subset from NIH PubChem, J.Chem.Inf.Model.,48, 2008, 465-475.
4 Yanli Wang, Jewen Xiao, Tugba O. Suzek, Jian Zhang, Jiyao Wang, and Stephen H. Bryant Nucleic Acids Res., 37, 2009, W623–W633.
5 Yanli Wang, Evan Bolton, Svetlana Dracheva, Karen Karapetyan, Benjamin A. Shoemaker, Tugba O. Suzek, Jiyao Wang, Jewen Xiao, Jian Zhang, and Stephen H. Bryant, Nucleic Acids Res. 38, 2010, D255-D266.
6 I.E.Weidlich,Igor V. Filippov, Jodian Brown, Neerja Kaushik-Basu, Ramalingam Krishnan, Marc C. Nicklaus, Ian F. Thorpe: Inhibitors for the hepatitis C virus RNA polymerase explored by SAR with advanced machine learning methods, Bioorg.Med.Chem., 2013 (http://www.sciencedirect.com/science/article/pii/S0968089613002460).