Tuttle Lisa M, Klevit Rachel E, Guttman Miklos
Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.
Department of Medicinal Chemistry, University of Washington, Seattle, WA 98195, USA.
bioRxiv. 2025 Mar 15:2025.03.13.643099. doi: 10.1101/2025.03.13.643099.
We present pyHXExpress, a customizable codebase for automated high-throughput multimodal analysis of all spectra generated from HDX-MS experiments. The workflow was validated against a synthetic test dataset to test the fitting algorithms and to confirm the statistical outputs. We further establish a framework for the determination of multimodality throughout a protein system by rigorous evaluation of multimodal fits across all peptide spectra. We demonstrate this approach using entire protein datasets to detect multimodality, conformational heterogeneity, and characterize dynamics of small heat shock protein HSPB5 and two disease mutants.
我们展示了pyHXExpress，这是一个可定制的代码库，用于对HDX-MS实验产生的所有光谱进行自动化高通量多模态分析。该工作流程针对一个合成测试数据集进行了验证，以测试拟合算法并确认统计输出。我们还通过对所有肽段光谱的多模态拟合进行严格评估，建立了一个用于确定整个蛋白质系统多模态的框架。我们使用完整的蛋白质数据集来检测多模态、构象异质性，并表征小分子热休克蛋白HSPB5及其两个疾病突变体的动力学，以此证明了这种方法。
