D3R Grand Challenge 4: ligand similarity and MM-GBSA-based pose prediction and affinity ranking for BACE-1 inhibitors.

ABSTRACT: The Drug Design Data Resource (D3R) Grand Challenges present an opportunity to assess, in the context of a blind predictive challenge, the accuracy and the limits of tools and methodologies designed to help guide pharmaceutical drug discovery projects. Here, we report the results of our participation in the D3R Grand Challenge 4 (GC4), which focused on predicting the binding poses and affinity ranking for compounds targeting the [Formula: see text]-amyloid precursor protein (BACE-1). Our ligand similarity-based protocol using HYBRID (OpenEye Scientific Software) successfully identified poses close to the native binding mode for most of the ligands with less than 2 Å RMSD accuracy. Furthermore, we compared the performance of our HYBRID-based approach to that of AutoDock Vina and DOCK 6 and

SUBMITTER: Sasmal S 

PROVIDER: S-EPMC8208075 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature