# Molecular Structure Determination by Mass Spectrometry and Computational Modeling > **NIH NIH R01** · UNIVERSITY OF MISSISSIPPI · 2020 · $447,312 ## Abstract PROJECT SUMMARY/ABSTRACT Structural biology plays a central role in modern molecular bioscience, enabling both a greater understanding and new mechanisms of manipulation of biomolecular action. However, despite tremendous development in tools for the generation of high resolution molecular models, large families of proteins are still poorly represented in databases of protein structure due to limitations of current technology. One method that has been used successfully to qualitatively study the structure of several of these families is hydroxyl radical protein footprinting (HRPF). HRPF is an emerging technology that has been used to study changes in protein topography by measuring changes in the apparent rate of reaction between hydroxyl radicals generated in situ and amino acid side chains on the protein surface. While this technology has been used successfully to study challenging problems in protein structure (e.g. membrane protein topography, glycoprotein-protein interactions, protein oligomerization and aggregation, protein interactions with heterogeneous ligand mixtures), such studies have always been comparative, detecting relative changes in protein topography from one conformation to another. Quantitative descriptions of protein structure have not been achieved due to a lack of knowledge of the link between HRPF reactivities and biophysical properties of the protein. Here, we propose to leverage preliminary data to develop amino acid-resolution HRPF (HR-HRPF) into a quantitative measurement of protein topography, accurately measuring the average solvent accessible surface areas () of many individual amino acids in YafO, a protein of unknown structure. By combining this data with a variety of de novo computational modeling strategies, we will generate accurate molecular models of protein structure using mass spectrometry data, testing these models against a structure of the same protein determined by NMR in a blinded fashion (in collaboration with Prof. James Prestegard, University of Georgia). We will also expand our chemistry and understanding to integral membrane proteins, developing the radical dosimetry technology and determining the empirical relationships between and HR-HRPF reactivity requires for quantitative measurements and modeling of integral membrane protein structure using bacteriorhodopsin as a model for technology development. Finally, we will develop technology and software tools to disseminate HR-HRPF technology into the broader biochemistry community, working with an established biochemistry group (Prof. Evgeny Nudler, NYUMC) to ensure technologies developed are robust and user-friendly. Together, these advances will add a new method for quantitative determination of protein structure and generation of accurate molecular models using protein chemistry and mass spectrometry. ## Key facts - **NIH application ID:** 9882525 - **Project number:** 5R01GM127267-03 - **Recipient organization:** UNIVERSITY OF MISSISSIPPI - **Principal Investigator:** Joshua S Sharp - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $447,312 - **Award type:** 5 - **Project period:** 2018-06-01 → 2022-02-28 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9882525 ## Citation > US National Institutes of Health, RePORTER application 9882525, Molecular Structure Determination by Mass Spectrometry and Computational Modeling (5R01GM127267-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9882525. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*