DiffBindFR: an SE(3) equivariant network for flexible protein-ligand docking.

ABSTRACT: Molecular docking, a key technique in structure-based drug design, plays pivotal roles in protein-ligand interaction modeling, hit identification and optimization, in which accurate prediction of protein-ligand binding mode is essential. Conventional docking approaches perform well in redocking tasks with known protein binding pocket conformation in the complex state. However, in real-world docking scenario without knowing the protein binding conformation for a new ligand, accurately modeling the binding complex structure remains challenging as flexible docking is computationally expensive and inaccurate. Typical deep learning-based docking methods do not explicitly consider protein side chain conformations and fail to ensure the physical plausibility and detailed atomic interactions. In t

SUBMITTER: Zhu J 

PROVIDER: S-EPMC11134415 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature