End-to-End Reverse Screening Identifies Protein Targets of Small Molecules Using HelixFold3
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Abstract (arXiv)
Identifying protein targets for small molecules, or reverse screening, is essential for understanding drug action, guiding compound repurposing, predicting off-target effects, and elucidating the molecular mechanisms of bioactive compounds. Despite its critical role, reverse screening remains challenging because accurately capturing interactions between a small molecule and structurally diverse proteins is inherently complex, and conventional step-wise workflows often propagate errors across decoupled steps such as target structure modeling, pocket identification, docking, and scoring. Here, we present an end-to-end reverse screening strategy leveraging HelixFold3, a high-accuracy biomolecular structure prediction model akin to AlphaFold3, which simultaneously models the folding of proteins from a protein library and the docking of small-molecule ligands within a unified framework. We validate this approach on a diverse and representative set of approximately one hundred small molecules. Compared with conventional reverse docking, our method improves screening accuracy and demonstrates enhanced structural fidelity, binding-site precision, and target prioritization. By systematically linking small molecules to their protein targets, this framework establishes a scalable and straightforward platform for dissecting molecular mechanisms, exploring off-target interactions, and supporting rational drug discovery.
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References · 6
- 2022DiffDock: Diffusion Steps, Twists, and Turns for Molecular Dockingcited by 313
- 2022State-specific protein-ligand complex structure prediction with a multi-scale deep generative modelcited by 35
- 2022E3Bind: An End-to-End Equivariant Network for Protein-Ligand Dockingcited by 35
- 2024Technical Report of HelixFold3 for Biomolecular Structure Predictioncited by 6
- 2024One-step Structure Prediction and Screening for Protein-Ligand Complexes using Multi-Task Geometric Deep Learningcited by 1
- 2024COMET:Combined Matrix for Elucidating Targetscited by 1
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