Computational and statistical methods for high-throughput analysis of post-translational modifications of proteins

Veit Schwämmle; Thiago Verano-Braga; Peter Roepstorff

doi:10.1016/j.jprot.2015.07.016

Computational and statistical methods for high-throughput analysis of post-translational modifications of proteins

J Proteomics. 2015 Nov 3:129:3-15. doi: 10.1016/j.jprot.2015.07.016. Epub 2015 Jul 26.

Authors

Veit Schwämmle¹, Thiago Verano-Braga², Peter Roepstorff³

Affiliations

¹ Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark. Electronic address: veits@bmb.sdu.dk.
² Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark; National Institute of Science and Technology in Nanobiopharmaceutics (INCT-Nanobiofar), Department of Physiology and Biophysics, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
³ Protein Research Group, Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark.

PMID: 26216596
DOI: 10.1016/j.jprot.2015.07.016

Abstract

The investigation of post-translational modifications (PTMs) represents one of the main research focuses for the study of protein function and cell signaling. Mass spectrometry instrumentation with increasing sensitivity improved protocols for PTM enrichment and recently established pipelines for high-throughput experiments allow large-scale identification and quantification of several PTM types. This review addresses the concurrently emerging challenges for the computational analysis of the resulting data and presents PTM-centered approaches for spectra identification, statistical analysis, multivariate analysis and data interpretation. We furthermore discuss the potential of future developments that will help to gain deep insight into the PTM-ome and its biological role in cells. This article is part of a Special Issue entitled: Computational Proteomics.

Keywords: Data analysis; Data interpretation; Multivariate analysis; Post-translational modification; Statistics.

Publication types

Research Support, Non-U.S. Gov't
Review

MeSH terms

Algorithms
Computational Biology / methods
Data Interpretation, Statistical
High-Throughput Screening Assays / methods*
Mass Spectrometry / methods*
Peptide Mapping / methods
Protein Processing, Post-Translational / physiology*
Proteins / chemistry*
Proteins / metabolism*
Sequence Analysis, Protein / methods*

Substances

Proteins