Combined SVM-based and docking-based virtual screening for retrieving novel inhibitors of c-Met
Qing-Qing Xie1, Lei Zhong, You-Li Pan
1State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, West China Medical School, Sichuan University, No 1, Keyuan 4 Road, High Tech Park, Chengdu, Sichuan 610041, China.
Abstract:
Aberrant c-Met activation has been demonstrated to be implicated in tumorigenesis and anti-cancer drug resistance. Discovery of c-Met inhibitors has attracted much attention in recent years. In this study, a support vector machine (SVM) classification model that discriminates c-Met inhibitors and non-inhibitors was first developed. Evaluation through screening a test set indicates that combined SVM-based and docking-based virtual screening (SB/DB-VS) considerably increases hit rate and enrichment factor compared with the individual methods. Thus the combined SB/DB-VS approach was adopted to screen PubChem, Specs, and Enamine for c-Met inhibitors. 75 compounds were selected for in vitro assays. Eight compounds display a good inhibitory potency against c-Met. Five of them are found to have novel scaffolds, implying a good potential for further chemical modification.
