OpenProt 2.0 builds a path to the functional characterization of alternative proteins
Sébastien Leblanc1, Feriel Yala1, Nicolas Provencher1
1Department of Biochemistry and Functional Genomics, Université de Sherbrooke, 3201 Jean Mignault, Sherbrooke, QC J1E 4K8, Canada.
Nucleic Acids Research
|November 13, 2023
Summary
OpenProt is a free resource for alternative open reading frames (AltORFs) and their protein sequences. This update adds new functional predictions and tools to explore the cryptic proteome.
Area of Science:
- Proteogenomics
- Bioinformatics
Background:
- The OpenProt resource provides access to alternative open reading frames (AltORFs) and their protein sequences.
- Standard databases often miss these cryptic proteomic elements.
Purpose of the Study:
- To enhance the OpenProt resource with new features based on user feedback.
- To improve the exploration and study of the cryptic proteome.
Main Methods:
- Implemented machine learning algorithms for predicting protein structure, subcellular localization, and intrinsic disorder.
- Integrated a machine learning-based peptide rescoring method into the mass spectrometry pipeline.
- Developed OpenCustomDB for custom protein database creation and OpenVar for genomic annotation of AltORFs.
Main Results:
- Introduced new functional annotations including structure, localization, and disorder predictions.
- Improved peptide identification accuracy in mass spectrometry.
- Enhanced data visualization with a new interface, spectral viewer, and multicoding gene predictions.
Conclusions:
- OpenProt is an evolving, freely accessible resource for proteogenomic research.
- The latest updates provide powerful new tools for discovering and analyzing novel proteins and AltORFs.
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