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BioinformaticsMolecular Omics
Peer-reviewed journal article

PTMscape: an open source tool to predict generic post-translational modifications and map hotspots of modification crosstalk

Ginny Xiaohe LiiD, Christine VogeliD, Hyungwon ChoiiD

Abstract

While tandem mass spectrometry can now detect post-translational modifications (PTM) at the proteome scale, reported modification sites are often incomplete and include false positives. Computational approaches can complement these datasets by additional predictions, but most available tools are tailored for single modifications and each tool uses different features for prediction. We developed an R package called PTMscape which predicts modifications sites across the proteome based on a unified and comprehensive set of descriptors of the physico-chemical microenvironment of modified sites, with additional downstream analysis modules to test enrichment of individual or pairs of modifications in functional protein regions. PTMscape is generic in the ability to process any major modifications, such as phosphorylation and ubiquitination, while achieving the sensitivity and specificity comparable to single-PTM methods and outperforming other multi-PTM tools. Maintaining generalizability of the framework, we expanded proteome-wide coverage of five major modifications affecting different residues by prediction and performed combinatorial analysis for spatial co-occurrence of pairs of those modifications. This analysis revealed potential modification hotspots and crosstalk among multiple PTMs in key protein domains such as histone, protein kinase, and RNA recognition motifs, spanning various biological processes such as RNA processing, DNA damage response, signal transduction, and regulation of cell cycle. These results provide a proteome-scale analysis of crosstalk among major PTMs and can be easily extended to other modifications.\n\nContactall correspondence should be addressed to hwchoi@nus.edu.sg.

PDFDOI

02 /Specification & Classification

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Citations
18
FWCI
0.89
Field percentile
top 29%

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