Optimization of compound ranking for structure-based virtual ligand screening using an established FRED-Surflex consensus approach.
The use of multiple target conformers has been applied successfully in virtual screening campaigns; however, a study on how to best combine scores for multiple targets in a hierarchic method that combines rigid and flexible docking is not available. In this study, we used a data set of 59 479 compounds to screen multiple conformers of four distinct protein targets to obtain an adapted and optimized combination of an established hierarchic method that employs the programs FRED and Surflex. Our study was extended and verified by application of our protocol to ten different data sets from the directory of useful decoys (DUD). We quantitated overall method performance in ensemble docking and compared several consensus scoring methods to improve the enrichment during virtual ligand screening. We conclude that one of the methods used, which employs a consensus weighted scoring of multiple target conformers, performs consistently better than methods that do not include such consensus scoring. For optimal overall performance in ensemble docking, it is advisable to first calculate a consensus of FRED results and use this consensus as a sub-data set for Surflex screening. Furthermore, we identified an optimal method for each of the chosen targets and propose how to optimize the enrichment for any target.
Department of Biochemistry, Cardiovascular Research Institute Maastricht, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, The Netherlands.
Jiangfeng
J
Du
Ivo W M
IW
Bleylevens
Albert V
AV
Bitorina
Kanin
K
Wichapong
Gerry A F
GA
Nicolaes
D015195:Drug Design; D062105:Molecular Docking Simulation; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D012372:ROC Curve; D012984:Software
D011506:Proteins
SB-VLS; consensus scoring; drug design; ensemble docking; virtual ligand screening