Drug discovery relies on efficient identification of small-molecule leads and their interactions with macromolecular targets. However, understanding how chemotypes impact mechanistically important conformational states often remains secondary among high-throughput discovery methods. Here, we present a conformational discovery pipeline integrating time-resolved, high-throughput small-angle X-ray scattering (TR-HT-SAXS) and classic fragment screening applied to allosteric states of the mitochondrial import oxidoreductase apoptosis-inducing factor (AIF). By monitoring oxidized and X-ray-reduced AIF states, TR-HT-SAXS leverages structure and kinetics to generate a multidimensional screening dataset that identifies fragment chemotypes allosterically stimulating AIF dimerization. Fragment-induced dimerization rates, quantified with time-resolved SAXS similarity analysis (k_VR), capture structure–activity relationships (SAR) across the top-ranked 4-aminoquinoline chemotype. Crystallized AIF–aminoquinoline complexes validate TR-SAXS-guided SAR, supporting this conformational chemotype for optimization. AIF–aminoquinoline structures and mutational analysis reveal active site F482 as an underappreciated allosteric stabilizer of AIF dimerization. This conformational discovery pipeline illustrates TR-HT-SAXS as an effective technology for targeting chemical leads to important macromolecular states.

药物发现依赖于小分子先导化合物及其与大分子靶标的相互作用的有效识别。然而，在高通量发现方法中，了解化学型如何影响机械上重要的构象状态通常仍然是次要的。在这里，我们提出了一个构象发现管道，集成了时间分辨、高通量小角度 X 射线散射 (TR-HT-SAXS) 和经典片段筛选，应用于线粒体输入氧化还原酶凋亡诱导因子 (AIF) 的变构状态。通过监测氧化和 X 射线还原的 AIF 状态，TR-HT-SAXS 利用结构和动力学生成多维筛选数据集，该数据集可识别变构刺激 AIF 二聚化的片段化学型。片段诱导的二聚化率通过时间分辨 SAXS 相似性分析 ( k _VR ) 进行量化，捕获排名靠前的 4-氨基喹啉化学型的结构-活性关系 (SAR)。结晶的 AIF-氨基喹啉复合物验证了 TR-SAXS 引导的 SAR，支持这种构象化学型的优化。 AIF-氨基喹啉结构和突变分析揭示活性位点 F482 作为 AIF 二聚化的一种未被充分认识的变构稳定剂。该构象发现流程表明 TR-HT-SAXS 是一种将化学先导化合物靶向重要大分子态的有效技术。