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A Hydrogen-Deuterium Exchange Mass Spectrometry HDX-MS Platform for Investigating Peptide Biosynthetic Enzymes
Published on: May 4, 2020
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A Functional Bayesian Model for Hydrogen-Deuterium Exchange Mass Spectrometry.
Oliver M Crook1, Nathan Gittens2, Chun-Wa Chung2
1Department of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom.
Journal of Proteome Research
|August 15, 2023
Summary
We introduce a flexible Bayesian framework for analyzing hydrogen-deuterium exchange mass spectrometry (HDX-MS) data. This approach enhances protein binding site identification and improves sensitivity in studying protein conformational changes.
Area of Science:
- Biochemistry
- Structural Biology
- Computational Biology
Background:
- Proteins undergo structural changes upon binding or environmental shifts.
- Hydrogen-deuterium exchange mass spectrometry (HDX-MS) tracks these conformational dynamics.
- Existing temporal analysis methods for HDX-MS have limitations in flexibility.
Purpose of the Study:
- To develop a more flexible and robust Bayesian framework for HDX-MS data analysis.
- To improve the statistical power and interpretability of HDX-MS experiments.
- To enhance the identification of protein-ligand or protein-protein interaction sites.
Main Methods:
- Reframing existing temporal analysis methods within a Bayesian statistical framework.
- Implementing algorithmic improvements for stability and uncertainty quantification.
- Applying the Bayesian approach to diverse HDX-MS datasets, including spike-in, epitope mapping, and small molecule binding studies.
Main Results:
- The Bayesian framework demonstrated improved algorithmic stability and uncertainty quantification.
- Rigorous model selection was achieved on a spike-in HDX-MS experiment.
- Enhanced interpretation in epitope mapping and increased sensitivity in a small molecule case study were observed.
- Identification of multiple interaction interfaces in an antibody dimer-E3 ubiquitin ligase complex, consistent with structural data.
Conclusions:
- The proposed Bayesian framework offers a flexible and powerful alternative for HDX-MS data analysis.
- This approach enhances the ability to identify protein interaction sites and study conformational dynamics.
- The method provides increased sensitivity and more reliable interpretation of complex biological systems.
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