Computational Studies to Improve Understanding and Outcomes of Covalent Labeling Mass Spectrometry Measurements

在化学系化学测量和成像计划的支持下，俄亥俄州立大学的Steffen Lindert和他的团队正在努力了解和改进共价标记蛋白质的质谱学(MS)测量。蛋白质上可接近的位置与特定标记的化学反应，然后使用MS来识别标记的区域，有助于阐明蛋白质的构象。林德特博士将进行分子动力学模拟，以了解标记试剂如何与蛋白质相互作用，以及它们是否会引起不必要的构象变化。此外，还将开发一台网络服务器，以确定给定蛋白质序列的最佳共价标记试剂。这些研究旨在改进MS共价标记测量，并通过这种方式更好地了解蛋白质构象，在蛋白质构象/折叠研究中具有潜在的长期科学影响。如果成功，这些研究将支持微创共价标记试剂的工作，并支持设计不扭曲被探测结构的新标记试剂。通过更好地了解共价标记试剂如何与蛋白质相互作用，以及通过系统地了解哪些标记最适合研究中的特定蛋白质，将极大地提高MS共价标记测量的性能和实用性。为了解决这些需求，需要持续的计算工作来推进共价标记测量科学。林德特博士的研究有望通过解决这些目前的局限性，进一步改进共价标记测量。分子动力学模拟将被用来开发不同的共价标记如何与蛋白质相互作用的更好模型。几个常用的共价标记与溶液中蛋白质的相互作用将被模拟在共价连接之前和之后，Lindert小组将探索某些标记是否以及可能如何扭曲蛋白质的结构或动力学。从这些模拟中获得的知识有可能提高对共价标记测量的理解。蛋白质序列定义了可能的结构构象，阐明了哪些残基可能是结构确定研究中标记的最佳残基。随后，将开发一个网络服务器来为给定的蛋白质序列确定最佳的共价标记试剂。该网络服务器的预计开发将使整个蛋白质共价标记社区受益。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Steffen Lindert and his group at Ohio State University are working to understand and improve mass spectrometry (MS) measurements of covalently labeled proteins. Chemical reactions of accessible sites on a protein with specific labels followed by the use of MS to identify the areas that were labeled helps illuminate protein conformation. Dr. Lindert will perform molecular dynamics simulations to understand how labeling reagents interact with proteins and whether they might induce unwanted conformational changes. Additionally, a web server will be developed to identify the optimal covalent labeling reagents for a given protein sequence. These studies are designed to improve MS covalent labeling measurements, and in this way lead to a better understanding of protein conformation, with potentially broad long term scientific impact in protein conformational/folding studies. If successful, these studies will support work with minimally invasive covalent labeling reagents and support the design of new labeling reagents that do not distort the probed structure. The performance and utility of MS covalent labeling measurements would be greatly improved by a better understanding of how covalent labeling reagents interact with proteins and through a systematic understanding of which labels are most suited for a particular protein under investigation. To address these needs, continued computational work that advances covalent labeling measurement science is required. Dr. Lindert’s research is expected to further improve covalent labeling measurements by addressing these current limitations. MD simulations will be used to develop better models of how different covalent labels interact with proteins. The interaction of several commonly used covalent labels with proteins in solution will be simulated before and after covalent attachment, and the Lindert group will explore if and potentially how certain labels distort protein structure or dynamics. Knowledge gained from these simulations has the potential to elevate understanding of covalent labeling measurements. The protein sequence defines possible structural conformations, illuminating which residues may be optimal for labeling in structure determination studies. Subsequently, a web server will be developed to identify the optimal covalent labeling reagents for a given protein sequence. The projected development of this web server stands to benefit the entire protein covalent-labeling community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.