Protein-ligand pose and affinity prediction: Lessons from D3R Grand Challenge 3.

ABSTRACT: We report the performance of HADDOCK in the 2018 iteration of the Grand Challenge organised by the D3R consortium. Building on the findings of our participation in last year's challenge, we significantly improved our pose prediction protocol which resulted in a mean RMSD for the top scoring pose of 3.04 and 2.67 Å for the cross-docking and self-docking experiments respectively, which corresponds to an overall success rate of 63% and 71% when considering the top1 and top5 models respectively. This performance ranks HADDOCK as the 6th and 3rd best performing group (excluding multiple submissions from a same group) out of a total of 44 and 47 submissions respectively. Our ligand-based binding affinity predictor is the 3rd best predictor overall, behind only the two leading structure-based imp

SUBMITTER: Koukos PI 

PROVIDER: S-EPMC6373529 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature