PTMScout, a Web resource for analysis of high throughput post-translational proteomics studies.

TitlePTMScout, a Web resource for analysis of high throughput post-translational proteomics studies.
Publication TypeJournal Article
Year of Publication2010
AuthorsNaegle, KM, Gymrek, M, Joughin, BA, Wagner, JP, Welsch, RE, Yaffe, MB, Lauffenburger, DA, White, FM
JournalMol Cell Proteomics
Volume9
Issue11
Pagination2558-70
Date Published2010 Nov
ISSN1535-9484
KeywordsAmino Acid Sequence, Databases, Protein, High-Throughput Screening Assays, Internet, Molecular Sequence Data, Protein Processing, Post-Translational, Proteins, Proteomics, Software
Abstract

The rate of discovery of post-translational modification (PTM) sites is increasing rapidly and is significantly outpacing our biological understanding of the function and regulation of those modifications. To help meet this challenge, we have created PTMScout, a web-based interface for viewing, manipulating, and analyzing high throughput experimental measurements of PTMs in an effort to facilitate biological understanding of protein modifications in signaling networks. PTMScout is constructed around a custom database of PTM experiments and contains information from external protein and post-translational resources, including gene ontology annotations, Pfam domains, and Scansite predictions of kinase and phosphopeptide binding domain interactions. PTMScout functionality comprises data set comparison tools, data set summary views, and tools for protein assignments of peptides identified by mass spectrometry. Analysis tools in PTMScout focus on informed subset selection via common criteria and on automated hypothesis generation through subset labeling derived from identification of statistically significant enrichment of other annotations in the experiment. Subset selection can be applied through the PTMScout flexible query interface available for quantitative data measurements and data annotations as well as an interface for importing data set groupings by external means, such as unsupervised learning. We exemplify the various functions of PTMScout in application to data sets that contain relative quantitative measurements as well as data sets lacking quantitative measurements, producing a set of interesting biological hypotheses. PTMScout is designed to be a widely accessible tool, enabling generation of multiple types of biological hypotheses from high throughput PTM experiments and advancing functional assignment of novel PTM sites. PTMScout is available at http://ptmscout.mit.edu.

DOI10.1074/mcp.M110.001206
Alternate JournalMol. Cell Proteomics
PubMed ID20631208
PubMed Central IDPMC2984232
Grant ListR01-CA096504 / CA / NCI NIH HHS / United States
U54-CA112967 / CA / NCI NIH HHS / United States