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Published on: August 2, 2018
IDPpub: Illuminating the Dark Phosphoproteome Through PubMed Mining
Sara R Savage1, Yaoyun Zhang2, Eric J Jaehnig1
1Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA.
This study introduces IDPpub, a deep learning tool that mines biomedical abstracts to identify and catalog thousands of phosphorylation sites. This resource enhances understanding of the phosphoproteome by providing crucial functional and contextual evidence for these sites.
Area of Science:
- Proteomics
- Bioinformatics
- Computational Biology
Background:
- Global phosphoproteomics yields vast data, but interpreting phosphorylation site functions and contexts remains challenging.
- Limited knowledge hinders understanding of biological roles and associated enzymes for identified phosphosites.
Purpose of the Study:
- To establish a comprehensive repository of phosphosites with associated evidence from biomedical literature.
- To leverage deep learning and natural language processing for mining the 'dark phosphoproteome'.
Main Methods:
- Fine-tuned BioBERT, a biomedical text mining tool, to create the IDPpub model.
- Extracted phosphorylation sites from MEDLINE abstracts, normalizing proteins to gene symbols and mapping sites to UniProt sequences.
- Validated model performance using curated abstracts and assessed utility with CPTAC and PhosphoSitePlus datasets.
Main Results:
- Achieved high precision (0.93) and recall (0.94) in cross-validation for substrate-phosphosite extraction.
- Independent validation demonstrated strong performance with 0.91 precision and 0.77 recall.
- Generated a repository of 18,458 human and 5918 mouse phosphosites with supporting evidence sentences.
Conclusions:
- IDPpub effectively extracts and compiles phosphosite information from biomedical literature.
- The IDPpub repository serves as a valuable resource, complementing existing databases and aiding phosphoproteome research.
- The automatically updatable repository offers a powerful tool for discovering and understanding phosphorylation site functions.
