Department of Chemistry, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States.
Department of Mathematical Sciences, School of Natural Sciences and Mathematics, University of Texas at Dallas, Richardson, Texas 75080, United States.
J Am Soc Mass Spectrom. 2020 Mar 4;31(3):658-665. doi: 10.1021/jasms.9b00132. Epub 2020 Jan 27.
The combination of covalent labeling (CL) and mass spectrometry (MS) has emerged as a useful tool for studying protein structure due to its good structural coverage, the ability to study proteins in mixtures, and its high sensitivity. Diethylpyrocarbonate (DEPC) is an effective CL reagent that can label N-termini and the side chains of several nucleophilic residues, providing information for about 30% of the residues in the average protein. For DEPC to provide accurate structural information, the extent of labeling must be controlled to minimize label-induced structural perturbations. In this work, we establish a quantitative correlation between general protein structural factors and DEPC reaction rates by measuring the reaction rate coefficients for several model proteins. Using principal component and regression analyses, we find that the solvent accessible surface areas of histidine and lysine residues in proteins are the primary factors that determine a protein's reactivity toward DEPC, despite the fact that other more abundant residues, such as tyrosine, threonine, and serine, are also labeled by DEPC. From the statistical analysis, a model emerges that can be used to predict the reactivity of a protein based on its structure and sequence, allowing the optimal DEPC concentration to be chosen for a given protein. The resulting model is supported by cross-validation studies and by accurately predicting of the reactivity of five test proteins. Overall, our model reveals interesting insight into the reactivity of proteins with DEPC, and it will facilitate identification of optimal DEPC labeling conditions for proteins.
共价标记（CL）和质谱（MS）的组合已成为研究蛋白质结构的有用工具，因为它具有良好的结构覆盖度、能够在混合物中研究蛋白质以及高灵敏度。焦碳酸二乙酯（DEPC）是一种有效的 CL 试剂，可标记 N-末端和几个亲核残基的侧链，为平均蛋白质中约 30%的残基提供信息。为了使 DEPC 提供准确的结构信息，必须控制标记程度以最小化标记引起的结构扰动。在这项工作中，我们通过测量几种模型蛋白的反应速率系数，建立了一般蛋白质结构因素与 DEPC 反应速率之间的定量相关性。通过主成分和回归分析，我们发现蛋白质中组氨酸和赖氨酸残基的溶剂可及表面积是决定蛋白质对 DEPC 反应性的主要因素，尽管其他更丰富的残基，如酪氨酸、苏氨酸和丝氨酸，也被 DEPC 标记。从统计分析中，出现了一种可以根据蛋白质的结构和序列来预测其反应性的模型，从而可以为给定的蛋白质选择最佳的 DEPC 浓度。该模型得到了交叉验证研究和对五个测试蛋白质反应性的准确预测的支持。总的来说，我们的模型揭示了蛋白质与 DEPC 反应性的有趣见解，并将有助于确定蛋白质的最佳 DEPC 标记条件。
