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mspms: A Comprehensive R Package and Graphic Interface for Multiplex Substrate Profiling by Mass Spectrometry Analysis

Charlie F. BayneiD, Brianna M. HurysziD, David J. GonzaleziD, Anthony John O’DonoghueiD

PDFDOI

Abstract

Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS) is a powerful method for determining the substrate specificity of proteolytic enzymes, knowledge key for developing protease inhibitors, diagnostics, and protease-activated therapeutics. However, the complex datasets generated by MSP-MS pose significant analytical challenges. To address this, we developed mspms, a Bioconductor R package complemented by an intuitive graphical interface. Mspms streamlines MSP-MS data analysis by standardizing workflows for data preparation, processing, statistical analysis, and visualization. Designed for accessibility, it serves both advanced users via the R package and broader audiences through the web interface. We validated mspms by profiling the substrate specificity of four well-characterized cathepsins (A-D), demonstrating its ability to reliably capture expected substrate specificities. As the first publicly available platform for MSP-MS data analysis, mspms delivers comprehensive functionality, transparency, and ease of use, making it a valuable resource for the protease research community. Access to mspms is available through the Bioconductor project at https://bioconductor.org/packages/mspms, and a graphic interface is available at https://gonzalezlab.shinyapps.io/mspms_shiny/. Author SummaryWe developed mspms, an easy-to-use tool that helps researchers analyze data from a proteomics technique called Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS). This software improves on previous methods of analyzing MSP-MS data, which required the user to navigate a confusing mix of R scripts, manual manipulation of spreadsheets, and third-party tools--an approach that was daunting for collaborators and new graduate students alike. Mspms streamlines the process, enabling faster, more reliable, and reproducible data analysis. We tested the tool using well-known proteases and found that it accurately identifies their known targets. As the first comprehensive tool for MSP-MS analysis, mspms makes this method approachable to a wider audience. Its available for free through the Bioconductor project at https://bioconductor.org/packages/mspms, and a graphical interface is available at https://gonzalezlab.shinyapps.io/mspms_shiny/.

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