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PPIP: Automated Software for Identification of Bioactive Endogenous Peptides.

Mingqiang Rong1, Baojin Zhou2, Ruo Zhou2

  • 1The National & Local Joint Engineering Laboratory of Animal Peptide Drug Development, College of Life Sciences , Hunan Normal University , Changsha 410081 , Hunan , China.

Journal of Proteome Research
|December 13, 2018
PubMed
Summary

We developed PPIP, a new software for identifying endogenous peptides using peptidomics and RNA-Seq data. This tool automates key steps in peptidogenomics analysis, improving large-scale peptide detection.

Keywords:
bioinformaticspeptidogenomicspeptidomicsproteogenomicsproteomics

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Genomics

Background:

  • Endogenous peptides are crucial for biological processes across species.
  • Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is vital for large-scale peptide detection.

Purpose of the Study:

  • To introduce PPIP, a specialized software for endogenous peptide identification.
  • To integrate peptidomics and RNA-Seq data for comprehensive peptidogenomics analysis.

Main Methods:

  • Automated de novo transcript assembly from RNA-Seq data.
  • Construction of protein reference databases from assembled transcripts.
  • Peptide identification and functional analysis using integrated components.
  • Containerization of software components using Docker technology.

Main Results:

  • PPIP enables automated de novo transcript assembly and protein database construction.
  • The software facilitates efficient peptide identification and functional annotation.
  • An HTML-based report generation feature is included for user-friendly output.

Conclusions:

  • PPIP offers a streamlined and automated solution for peptidogenomics research.
  • The software enhances the identification and analysis of endogenous peptides.
  • PPIP is accessible via Docker Hub and GitHub, with a user manual available.