Learning from the ligand: using ligand-based features to improve binding affinity prediction

Machine learning scoring functions for protein-ligand binding affinity prediction have been found to consistently outperform classical scoring functions. Structure-based scoring functions for universal affinity prediction typically use features describing interactions derived from the protein-ligand...

詳細記述

書誌詳細
主要な著者: Boyles, F, Deane, C, Morris, G
フォーマット: Journal article
出版事項: 2019