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Related Experiment Video

Updated: Jun 1, 2025

Profiling Ubiquitin and Ubiquitin-like Dependent Post-translational Modifications and Identification of Significant Alterations
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A computational tool to infer enzyme activity using post-translational modification profiling data.

Dehui Kong1,2, Aijun Zhang1,2, Ling Li1,2

  • 1Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN, USA.

Communications Biology
|January 21, 2025
PubMed
Summary

We developed JUMPsem, a computational tool to infer enzyme activity from post-translational modification data. This method accurately estimates kinase, E3 ligase, and HAT activities, outperforming existing tools.

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Proteomics

Background:

  • Enzymes are crucial for cellular signaling, but their activity measurement is challenging and often indirect.
  • Current methods struggle to infer enzyme activity directly from large-scale post-translational modification (PTM) data.
  • High-throughput proteomics typically measures protein abundance, not functional activity.

Purpose of the Study:

  • To introduce JUMPsem, a novel computational tool for inferring enzyme activity from PTM profiling data.
  • To enable the estimation of specific enzyme classes, including kinases, ubiquitin E3 ligases, and histone acetyltransferases (HATs).
  • To establish new enzyme-substrate relationships and improve the analysis of enzyme function.

Main Methods:

  • Utilized structural equation modeling (SEM) under the JUMP framework.
  • Applied JUMPsem to phosphoproteome, ubiquitinome, and acetylome data.
  • Developed motif searching capabilities for novel enzyme-substrate relationship discovery.

Main Results:

  • JUMPsem successfully estimated kinase, ubiquitin E3 ligase, and HAT activities.
  • The tool identified novel enzyme-substrate relationships by analyzing motif sequences.
  • JUMPsem demonstrated superior performance compared to IKAP and KSEA in kinase activity prediction, offering greater speed and scope.

Conclusions:

  • JUMPsem provides a robust and scalable method for inferring protein enzyme activities from PTM data.
  • The open-source R package and R/Shiny app enhance accessibility for researchers.
  • JUMPsem has the potential to advance drug development by improving the understanding of enzyme function.