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Inflect: Optimizing Computational Workflows for Thermal Proteome Profiling Data Analysis.

Neil A McCracken1, Sarah A Peck Justice1, Aruna B Wijeratne1

  • 1Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States.

Journal of Proteome Research
|March 4, 2021
PubMed
Summary

Optimizing data analysis for CETSA and Thermal Proteome Profiling (TPP) is crucial for drug discovery. This study details a user-friendly workflow, Inflect, to improve the identification of protein stabilization and destabilization from proteomics data.

Keywords:
CETSAInflectLC-MS/MSTPPprotein stabilityprotein−protein interactionproteomics

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Area of Science:

  • Proteomics
  • Biochemistry
  • Pharmacology

Background:

  • Cellular thermal shift assay (CETSA) and Thermal Proteome Profiling (TPP) are vital for studying protein-ligand interactions and stability.
  • These methods are increasingly used in signaling research and drug discovery.
  • Optimizing data analysis for these techniques is essential for accurate results.

Purpose of the Study:

  • To optimize the data analysis pipeline for calculating protein melt temperatures (Tm) and melt shifts from proteomics data.
  • To describe the impact of individual calculation steps on the identification of stabilized and destabilized proteins.
  • To develop and provide a user-friendly, optimized analysis workflow for TPP and CETSA data.

Main Methods:

  • Analysis of the melt shift calculation workflow, detailing the impact of each step.
  • Development of an optimized analysis workflow based on identified key steps.
  • Creation of an R-based program, Inflect, for melt curve fitting and melt shift analysis.

Main Results:

  • The study quantifies how specific calculation steps influence the identification of stabilized/destabilized proteins.
  • An optimized analysis workflow was developed, demonstrating sensitivity to chosen calculation steps.
  • The Inflect R package provides melt curves and a data matrix compatible with downstream analysis tools like UpsetR.

Conclusions:

  • This work offers a valuable resource for scientists analyzing TPP and CETSA data.
  • The optimized workflow and Inflect package enhance the identification of biologically relevant protein changes.
  • The findings facilitate the implementation of tailored analysis pipelines for specific research applications.