Using phosphoproteomics data to understand cellular signaling: a comprehensive guide to bioinformatics resources

Clinical Proteomics
Sara R Savage, Bing Zhang

Abstract

Mass spectrometry-based phosphoproteomics is becoming an essential methodology for the study of global cellular signaling. Numerous bioinformatics resources are available to facilitate the translation of phosphopeptide identification and quantification results into novel biological and clinical insights, a critical step in phosphoproteomics data analysis. These resources include knowledge bases of kinases and phosphatases, phosphorylation sites, kinase inhibitors, and sequence variants affecting kinase function, and bioinformatics tools that can predict phosphorylation sites in addition to the kinase that phosphorylates them, infer kinase activity, and predict the effect of mutations on kinase signaling. However, these resources exist in silos and it is challenging to select among multiple resources with similar functions. Therefore, we put together a comprehensive collection of resources related to phosphoproteomics data interpretation, compared the use of tools with similar functions, and assessed the usability from the standpoint of typical biologists or clinicians. Overall, tools could be improved by standardization of enzyme names, flexibility of data input and output format, consistent maintenance, and detailed manuals.

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Citations

Sep 18, 2020·Proteomics·Bo WenBing Zhang
Oct 31, 2020·International Journal of Molecular Sciences·Kristyna BarvikovaViktorie Vlachova
Jun 12, 2021·PeerJ·Hannah HuckstepMelissa J Davis
Sep 2, 2021·Expert Review of Proteomics·Jacqueline S Gerritsen, Forest M White

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Software Mentioned

Scansite
PhosphoAtlas
DynaPho
Windows
OMICtools
Swiss
RLIMS
eFIP
GPS
RegPhos

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