Rescoring and Linearly Combining: A Highly Effective Consensus Strategy for Virtual Screening Campaigns.

ABSTRACT: The study proposes a novel consensus strategy based on linear combinations of different docking scores to be used in the evaluation of virtual screening campaigns. The consensus models are generated by applying the recently proposed Enrichment Factor Optimization (EFO) method, which develops the linear equations by exhaustively combining the available docking scores and by optimizing the resulting enrichment factors. The performances of such a consensus strategy were evaluated by simulating the entire Directory of Useful Decoys (DUD datasets). In detail, the poses were initially generated by the PLANTS docking program and then rescored by ReScore+ with and without the minimization of the complexes. The so calculated scores were then used to generate the mentioned consensus models including

SUBMITTER: Pedretti A 

PROVIDER: S-EPMC6540224 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature