Bioinformatics analysis and prediction of protein phosphorylation and other posttranslational modifications

Abstract

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Protein posttranslational modifications (PTM), such as phosphorylation, play essential roles in many aspects of cell life. With the rapid accumulation of PTM sites in the past decade, thanks to high-throughput proteomics studies, bioinformatics is becoming essential to manage the data and mine the underlying biological meaning. Our study on phosphorylation and other PTMs has yielded three bioinformatics tools: P3DB, Musite, and protmod. P3DB is a web-based database hosting protein phosphorylation data in multiple plants. With the user friendly web interface and embedded search and BLAST tools, P3DB provides a useful resource for researchers to browse, query and compare phosphorylation data. Musite is an open source platform for large scale prediction of phosphorylation sites. We collected phosphoproteomics data in multiple organisms from several reliable sources and used them to train prediction models by a comprehensive machine-learning approach that integrates local sequence similarities to known phosphorylation sites, protein disorder scores, and amino acid frequencies. Cross validation test results showed that Musite outperformed previous phosphorylation prediction tools. A web server version, Musite.net, is also being developed. Protmod is a BioJava package for identification of PTMs from 3-D structures in PDB. It supports identification of more than 200 different types of PTMs, such as phosphorylation, glycosylation, and disulfide bonds.