Improving Structure-Based Virtual Screening with Ensemble Docking and Machine Learning.

ABSTRACT: One of the main challenges of structure-based virtual screening (SBVS) is the incorporation of the receptor's flexibility, as its explicit representation in every docking run implies a high computational cost. Therefore, a common alternative to include the receptor's flexibility is the approach known as ensemble docking. Ensemble docking consists of using a set of receptor conformations and performing the docking assays over each of them. However, there is still no agreement on how to combine the ensemble docking results to obtain the final ligand ranking. A common choice is to use consensus strategies to aggregate the ensemble docking scores, but these strategies exhibit slight improvement regarding the single-structure approach. Here, we claim that using machine learning (ML) methodologi

SUBMITTER: Ricci-Lopez J 

PROVIDER: S-EPMC8865842 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature