Dhar Anjali, Sisk Thomas R, Robustelli Paul
Department of Chemistry, Dartmouth College, Hanover, New Hampshire 03755, United States.
J Chem Inf Model. 2025 Jul 14;65(13):6847-6860. doi: 10.1021/acs.jcim.5c00370. Epub 2025 Jun 18.
Intrinsically disordered proteins (IDPs) are implicated in many human diseases and are increasingly being pursued as drug targets. Conventional structure-based drug design methods that rely on well-defined binding sites are, however, largely unsuitable for IDPs. Here, we present computationally efficient ensemble docking approaches to predict the relative affinities of small molecules to IDPs and characterize their dynamic, heterogeneous binding mechanisms at atomic resolution. We show that these ensemble docking protocols accurately predict the relative binding affinities of three small molecule α-synuclein ligands measured by NMR spectroscopy and generate conformational ensembles of ligand binding modes in remarkable agreement with experimentally validated long-time scale molecular dynamics simulations of ligand binding. Our results demonstrate the potential of ensemble docking approaches for predicting small molecule binding to IDPs and suggest that these methods may be valuable tools for IDP drug discovery campaigns.
内在无序蛋白质（IDP）与许多人类疾病有关，并且越来越多地被作为药物靶点进行研究。然而，依赖于明确结合位点的传统基于结构的药物设计方法在很大程度上不适用于IDP。在这里，我们提出了计算效率高的整体对接方法，以预测小分子与IDP的相对亲和力，并在原子分辨率下表征它们动态、异质的结合机制。我们表明，这些整体对接协议准确地预测了通过核磁共振光谱测量的三种小分子α-突触核蛋白配体的相对结合亲和力，并生成了配体结合模式的构象集合，与经过实验验证的配体结合长时间尺度分子动力学模拟结果非常一致。我们的结果证明了整体对接方法在预测小分子与IDP结合方面的潜力，并表明这些方法可能是IDP药物发现活动中的有价值工具。
