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Protein-ligand binding affinity prediction: Is 3D binding pose needed?
Open accessPreprint — published as 10.1038/s42004-025-01506-1 · Paper page
Abstract
Accurate protein-ligand binding affinity prediction is crucial in drug discovery. Existing methods are predominately docking-free, without explicitly considering atom-level interaction between proteins and ligands in scenarios where crystallized protein-ligand binding conformations are unavailable. Now, with breakthroughs in deep learning AI-based protein folding and binding conformation prediction, can we improve binding affinity prediction? This study introduces a framework, Folding-Docking-Affinity (FDA), which folds proteins, determines protein-ligand binding conformations and predicts binding affinities from three-dimensional protein-ligand binding structures. Our experiments demonstrate that the FDA outperforms state-of-the-art docking-free models in the DAVIS dataset, showcasing the potential of explicit modeling of three-dimensional binding conformations for enhancing binding affinity prediction accuracy.
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Citations
Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
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Metadata
- Authors
- Zhi, D., Wu, M. H., & Xie, Z.
- Affiliations
- The University of Texas Health Science Center at Houston (US)
- Corresponding author
- Zhi, Degui
- Wu, Ming Hsiu
- Venue
- Communications Chemistry
- Published
- 2024-05-06
- Volume
- 8
- Issue
- 1
- Pages
- 108-108
- ISSN
- 2399-3669 (ISSN-L)
- PMC
- PMC11977223
- OpenAlex
- W4409218613
- Cited by
- 19
- References
- 1
- Citations by year
- 2026: 13 · 2025: 6
- FWCI
- 9.78
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Communications Chemistry (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Research Square (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Interaction Studies and Fluorescence Analysis
- Keywords
- protein-ligand binding affinity prediction, protein folding, protein-ligand docking, drug discovery
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