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Can Deep Learning Methods Tackle Practical Protein-Ligand Docking Challenges? Introducing PoseBench
Scientists from the University of Missouri, Columbia introduced PoseBench, the first exhaustive benchmark for practical protein-ligand docking, enabling rigorous evaluation of deep learning docking methods on predicted protein structures, multiple concurrently binding ligands, and targets without known binding pockets. It introduces multi-ligand benchmark datasets and reveals limitations of current deep learning approaches in generalizing to…
