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Updated: Jan 26, 2026
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Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics
Published on: October 13, 2020
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mspms: an R package and GUI for multiplex substrate profiling by mass spectrometry
Charlie Bayne1,2, Brianna Hurysz3,4,5, David J Gonzalez4,5,6
1Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, 92093, USA. chbayne@health.ucsd.edu.
BMC Bioinformatics
|January 24, 2026
Summary
We developed mspms, an R package and web tool, to simplify the analysis of Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS) data. This tool makes complex protease substrate specificity analysis accessible to researchers.
Area of Science:
- Proteomics
- Enzymology
- Bioinformatics
Background:
- Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS) is crucial for understanding protease function.
- Analyzing complex MSP-MS datasets presents significant challenges for researchers.
- Limited accessibility of current MSP-MS analysis tools hinders broader adoption.
Purpose of the Study:
- To develop a user-friendly and comprehensive software solution for MSP-MS data analysis.
- To streamline the entire workflow from data preprocessing to visualization.
- To enhance accessibility for both expert and non-expert users in protease research.
Main Methods:
- Development of the 'mspms' R package and an accompanying graphical user interface (GUI).
- Implementation of standardized workflows for data preparation, processing, and statistical analysis.
- Validation using MSP-MS data from well-characterized cathepsins (A-D).
Main Results:
- The 'mspms' package and GUI provide a streamlined and accessible platform for MSP-MS data analysis.
- The tool successfully standardizes data workflows, including preprocessing, normalization, statistical testing, and visualization.
- Validation confirmed that 'mspms' accurately captures known substrate specificities for cathepsins.
Conclusions:
- 'mspms' is the first comprehensive, publicly available platform for post-identification MSP-MS data analysis.
- It offers an integrated, transparent, and user-friendly framework for protease research.
- The R package and online GUI facilitate wider use and advance the field of protease research.
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