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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
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.
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.
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