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| Funder | Engineering and Physical Sciences Research Council |
|---|---|
| Recipient Organization | University of Oxford |
| Country | United Kingdom |
| Start Date | Sep 30, 2022 |
| End Date | Sep 29, 2026 |
| Duration | 1,460 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2736597 |
Detailed information on the mechanism of activation is enigmatic for many proteins. Protein mechanism and function is a product of both the structure and the dynamics of the system. Dynamical behaviour is invisible to standard structural studies such as X-ray crystallography and CryoEM.
To improve our understanding of how protein drug targets respond to ligands requirements the development of methods that can probe dynamics. Hydrogen-Deuterium Exchange Mass-Spectrometry (HDX-MS) is a widely used experimental technique that provides quantitative information on the protein's amide hydrogen bonding network, thereby facilitating the exploration of protein conformational dynamics.
HDX-MS stands out to other complementary biophysical techniques as it has advantages over many other methods in that there is no limit to the size of protein it can study and it can probe proteins in conditions similar to the native environment. As such HDX-MS is extensively used in small molecule, antibody, and vaccine applications.
In small molecule research, HDX-MS can report on both direct binding events and allosteric modulation. In studies of conformational mechanism, the full deconvolution of HDX data into structural representation can be bypassed by restricting the conformational state of proteins. These sorts of experimental studies are often complemented by Molecular Dynamics (MD) simulations that can be used to monitor the conformational dynamics of proteins and their complexes.
The frequent use of HDX-MS in antibody therapeutics research underscores its position as a routinely utilized branch of Analytical Science. The experimental method combines Biological Informatics and Computational and Theoretical Chemistry. HDX-MS involves breaking down a protein into peptides, the peptide fragment/protein sequences must then be matched which can be challenging due to the number of different peptide/mass possibilities.
MD simulations are therefore used to help resolve gaps in the resulting data and to help relate the spatially distributed exchange rates to structural functions. As proteins are inherently Non-Linear Systems, the MD simulations require careful implementation to reweight the dynamical observations to simulated structures, to link dynamics to protein function.
Presently, two main regimes exist for performing HDX-MS studies: experiment rich and simulation rich. A primary research objective is to compare the two approaches and apply the latest techniques from both HDX-MS as well as MD simulation. This goal will be achieved by the combination interdisciplinary experience of the team: experimental HDX-MS (Srinath Krishnamurthy, OMass), computational chemistry (Maria Musgaard, OMass), theoretical methods in HDX-MS (Oliver Crook, Oxford) and structural biology and statistics (Charlotte Deane, Oxford).
In this project, we will develop an integrative approach between HDX-MS and MD to investigate the mechanism of activation of receptors with multiple small molecule modulators. Beyond simply contrasting best practices, one intriguing area we plan to explore is the Graphics and Visualisation of these data, the inherent high dimensionality can make interpretation challenging.
A wealth of HDX-MS data from published studies are available and provide a testbed to compare different approaches. In addition, OMass has several current studies for exploration as well as the possibility to supplement the data with further experiments. This will enable us to investigate the latest advancements in HDX-MS experiments.
Initially we will leverage the wealth of data generated in previous work on a library of structural dynamics from RORy modulators by HDX-MS (38 compounds studied via HDX-MS and around 60 pdb structures) to determine whether the correct protein-ligand complex conformations can be predicted or selected from MD trajectories attempting to reveal the conformational dynamics of activation.
University of Oxford
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