用端到端方法精准找到小分子靶蛋白,提升药物研发效率
End-to-End Reverse Screening Identifies Protein Targets of Small Molecules Using HelixFold3
- 用HelixFold3统一建模蛋白结构与小分子对接
- 在百余个分子上准确识别靶点,优于传统方法
- 适合药物重定位与副作用预测研究
确定小分子的蛋白靶点(反向筛选)对理解药物作用、指导化合物重定位、预测脱靶效应和解析生物活性化合物的分子机制至关重要。尽管如此,由于准确捕捉小分子与结构多样的蛋白质之间的相互作用本就复杂,且传统分步流程常在结构建模、结合口袋识别、对接与评分等环节传递误差,反向筛选仍具挑战。本文提出一种基于HelixFold3的端到端反向筛选策略,该模型可同时在统一框架内预测蛋白质折叠并完成小分子配体对接。我们在约一百个代表性小分子上验证了该方法,结果表明其相比传统反向对接显著提升了筛选准确性,展现出更高的结构保真度、结合位点精度和靶点排序能力。该框架系统性地将小分子与其蛋白靶点关联,为解析分子机制、探索脱靶相互作用及支持理性药物设计提供了可扩展、简便的平台。
原文摘要 · Abstract (English)
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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