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Powerful generative AI models of protein-ligand structure have recently been proposed, but few of these methods support both flexible protein-ligand docking and affinity estimation.
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A. Dhakal, C. McKay, and J. Cheng · 2022
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Evolutionary-scale prediction of atomic-level protein structure with a language model
Z. Lin, H. Akin, et al · 2023
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Posebusters: Ai-based docking methods fail to generate physically valid poses or generalise to novel sequences
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Casp16 abstracts
CASP16-Organizers · 2024
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Deep learning for protein-ligand docking: Are we there yet?
A. Morehead, N. Giri, J. Liu, and J. Cheng · 2024
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Z. Qiao, W. Nie, et al · 2024
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Harmonic self-conditioned flow matching for joint multi-ligand docking and binding site design
H. Stark, B. Jing, et al · 2024
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A. Tong, K. Fatras, and others · 2024
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J. Wohlwend, G. Corso, et al · 2024
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Protein-ligand structure and affinity prediction in casp16 using a geometric deep learning ensemble and flow matching
A. Morehead, J. Liu, P. Neupane, N. Giri, and J. Cheng · 2025
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