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

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.