A Diverse Benchmark Based on 3D Matched Molecular Pairs for Validating Scoring Functions.

ABSTRACT: The prediction of protein-ligand interactions and their corresponding binding free energy is a challenging task in structure-based drug design and related applications. Docking and scoring is broadly used to propose the binding mode and underlying interactions as well as to provide a measure for ligand affinity or differentiate between active and inactive ligands. Various studies have revealed that most docking software packages reliably predict the binding mode, although scoring remains a challenge. Here, a diverse benchmark data set of 99 matched molecular pairs (3D-MMPs) with experimentally determined X-ray structures and corresponding binding affinities is introduced. This data set was used to study the predictive power of 13 commonly used scoring functions to demonstrate the applicabi

SUBMITTER: Kalinowsky L 

PROVIDER: S-EPMC6641919 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature