Synergistic Application of Molecular Docking and Machine Learning for Improved Protein-Ligand Binding Pose Prediction
He Yang,
Hongrui Lin,
Yannan Yuan
et al.
Abstract:Accurate prediction of protein-ligand complex structures is a crucial step in structure-based drug design. Traditional molecular docking methods exhibit limitations in terms of accuracy and sampling space, while relying on machine-learning approaches may lead to invalid conformations. In this study, we propose a novel strategy that combines molecular docking and machine learning methods. Firstly, the protein-ligand binding poses are predicted using the Uni-Mol Docking machine learning approach. Subsequently, p… Show more
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