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Measuring protein structural changes on a proteome-wide scale using limited proteolysis-coupled mass spectrometry
Simone Schopper1, Abdullah Kahraman2, Pascal Leuenberger1
1Institute of Biochemistry, Department of Biology, ETH Zurich, Zurich, Switzerland.
Limited proteolysis-coupled mass spectrometry (LiP-MS) identifies protein structural changes in complex biological samples. This proteomics approach analyzes proteome-wide alterations for drug discovery and disease detection.
Area of Science:
- Proteomics
- Biophysics
- Molecular Biology
Background:
- Protein structural dynamics are crucial for cellular functions.
- Existing biophysical methods struggle to analyze proteome-wide structural changes in complex biological extracts.
- A need exists for methods to assess protein structural alterations within their native cellular environment.
Purpose of the Study:
- To introduce and validate Limited proteolysis-coupled mass spectrometry (LiP-MS) as a proteome-wide approach for detecting protein structural changes.
- To demonstrate the applicability of LiP-MS in complex biological contexts.
- To highlight the potential of LiP-MS for various biological and medical applications.
Main Methods:
- Proteome extracts undergo sequential protease digestion: non-specific protease under native conditions, followed by trypsin under denaturing conditions.
- Structure-specific peptides are generated for bottom-up mass spectrometry (MS) analysis.
- Label-free quantification via shotgun or targeted MS measures structure-dependent proteolytic patterns.
Main Results:
- LiP-MS enables the identification of protein structural alterations directly within complex biological extracts.
- The method allows for proteome-wide scale analysis of structural changes.
- Specific protein regions involved in structural transitions or affected by binding events can be identified.
Conclusions:
- LiP-MS is a powerful proteomics technique for analyzing protein structural changes in their native biological context.
- Applications include discovering perturbation-induced alterations, identifying drug targets, and detecting disease-associated protein structural states.
- The approach facilitates the study of protein aggregates and binding events directly in biological samples.
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