Moroco Jamie A, Jacome Alvaro Sebastian Vaca, Beltran Pierre Michel Jean, Reiter Andrew, Mundorff Charlie, Guttman Miklos, Morrow Jeff, Coales Stephen, Mayne Leland, Hamuro Yoshitomo, Carr Steven A, Papanastasiou Malvina
Broad Institute of MIT & Harvard, Cambridge, Massachusetts, USA.
Department of Medicinal Chemistry, University of Washington, Seattle, Washington, USA.
Mol Cell Proteomics. 2025 Feb;24(2):100904. doi: 10.1016/j.mcpro.2025.100904. Epub 2025 Jan 7.
Despite the widespread use of MS for hydrogen/deuterium exchange measurements, no systematic, large-scale study has been conducted to compare the observed exchange rates in protein-derived, unstructured peptides measured by MS to the predicted exchange rates calculated from NMR-derived values and how neighboring residues and post-translational modifications influence those exchange rates. In this study, we sought to test the accuracy of predicted values by performing hydrogen exchange measurements on whole cell digests to generate an unbiased dataset of 563 unique peptides derived from naturally occurring protein sequences. A remarkable 97% of observed exchange rates of peptides are within two-fold of predicted values. Using fully deuterated controls, we found that for approximately 50% of the peptides, the amino acid sequence and, consequently, the intrinsic exchange rate, are the primary contributors to back exchange. A meta-analysis of the remaining physicochemical properties of peptides revealed multiple features that contribute either positively or negatively to back exchange discrepancies. Employing our workflow for comparable measurements on synthetic peptide mixtures containing post-translational modifications, and their unmodified counterparts, we show that lysine acetylation has a strong effect on the observed exchange rate, whereas serine/threonine phosphorylation does not. Our automated workflow enables high-throughput determination of exchange rates in complex biological peptide mixtures with diverse properties.
尽管质谱(MS)在氢/氘交换测量中得到了广泛应用,但尚未进行系统的大规模研究,以比较通过质谱测量的蛋白质衍生无结构肽中观察到的交换率与根据核磁共振(NMR)衍生值计算出的预测交换率,以及相邻残基和翻译后修饰如何影响这些交换率。在本研究中,我们试图通过对全细胞消化物进行氢交换测量来测试预测值的准确性,以生成一个由563个源自天然蛋白质序列的独特肽组成的无偏数据集。肽的观察到的交换率中,有高达97%在预测值的两倍以内。使用完全氘代的对照,我们发现,对于大约50%的肽来说,氨基酸序列以及因此的内在交换率是反向交换的主要贡献因素。对肽的其余物理化学性质进行的荟萃分析揭示了多个对反向交换差异有正向或负向贡献的特征。利用我们的工作流程对含有翻译后修饰的合成肽混合物及其未修饰对应物进行可比测量,我们表明赖氨酸乙酰化对观察到的交换率有很强的影响,而丝氨酸/苏氨酸磷酸化则没有。我们的自动化工作流程能够高通量测定具有不同性质的复杂生物肽混合物中的交换率。