Department of Chemistry, York University, Toronto, ON M3J 1P3, Canada.
Structural Genomics Consortium, University of Toronto, Toronto, ON M5G 1L7, Canada.
Anal Chem. 2024 Aug 13;96(32):13015-13024. doi: 10.1021/acs.analchem.4c01001. Epub 2024 Jul 29.
Hydrogen-deuterium eXchange mass spectrometry (HDX-MS) is increasingly used in drug development to locate binding sites and to identify allosteric effects in drug/target interactions. However, the potential of this technique to quantitatively analyze drug candidate libraries remains largely unexplored. Here, a collection of 13 WDR5-targeting small molecules with surface plasmon resonance (SPR) dissociation coefficients () ranging from 20 nM to ∼116 μM were characterized using differential HDX-MS (ΔHDX-MS). Conventional qualitative analysis of the ΔHDX-MS data set revealed the binding interfaces for all compounds and allosteric effects where present. We then demonstrated that ΔHDX-MS signal-to-noise (S/N) not only can rank library-relative affinity but also can accurately predict from a calibration curve constructed from high-quality SPR data. Three methods for S/N calculation are explored, each suitable for libraries with different characteristics. Our results demonstrate the potential for ΔHDX-MS use in drug candidate library affinity validation and/or determination while simultaneously characterizing structure.
氢氘交换质谱(HDX-MS)技术在药物研发中被广泛应用于定位结合位点和识别药物/靶标相互作用中的变构效应。然而,该技术在定量分析候选药物库方面的潜力在很大程度上尚未得到探索。在这里,我们使用表面等离子体共振(SPR)解离系数()在 20 nM 至约 116 μM 范围内的 13 种 WDR5 靶向小分子进行了研究,这些小分子均采用差示 HDX-MS(ΔHDX-MS)进行了表征。通过对 ΔHDX-MS 数据集进行常规的定性分析,揭示了所有化合物的结合界面和变构效应(如果存在的话)。然后,我们证明了 ΔHDX-MS 的信噪比(S/N)不仅可以对库相对亲和力进行排序,而且可以根据从高质量 SPR 数据构建的校准曲线准确预测。我们探索了三种 S/N 计算方法,每种方法都适用于具有不同特征的文库。我们的研究结果表明,ΔHDX-MS 可用于候选药物库亲和力验证和/或测定,同时还可以对结构进行表征。