Format

Send to

Choose Destination
J Proteomics. 2018 Jan 16;171:116-126. doi: 10.1016/j.jprot.2017.04.011. Epub 2017 Apr 19.

Elucidation of the dynamic nature of interactome networks: A practical tutorial.

Author information

1
CNC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal; Faculty of Sciences and Technology, University of Coimbra, Coimbra, Portugal; CNC, IBILI, University of Coimbra, Coimbra, Portugal. Electronic address: sandra.isabel.anjo@gmail.com.
2
CNC, IBILI, University of Coimbra, Coimbra, Portugal; Institute of Biomedical Imaging and Life Sciences (IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal.
3
Centro de Estudos de Doenças Crónicas (CEDOC), NOVA Medical School, Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Lisboa, Portugal.
4
CNC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal.

Abstract

Considering that proteins are usually engaged in complex and dynamic networks of interactions to exert their activity, a way to understand proteins' functions and the molecular mechanisms in which those proteins are involved, is by studying their interactome. In this sense, this tutorial presents a simple pipeline for the analysis of the network of interactions of a protein in order to reach a biological interpretation of the mechanisms modulated by those interactions, and to understand how these interactions are affected by the experimental conditions. The entire pipeline is explained using as example the previously published work "Interacting network of the gap junction protein connexin43 is modulated by ischemia and reperfusion in the heart", and by using user-friendly and freely available software. Moreover, the pipeline presented in this article is not limited to interactomic approaches, being also useful for the analysis of dynamic alterations of other proteomic screenings.

SIGNIFICANCE:

This tutorial presents a simplified pipeline for the analysis of the network of interactions of a protein in order to reach to a biological interpretation of the mechanisms modulated by those interactions, which constitutes an important way to understand proteins' functions and the molecular mechanisms in which those proteins are involved. Moreover, when interactomics is applied to perform an in-depth molecular analysis of novel disease proteins, it can result in an understanding of disease-causing mechanisms and create drug discovery opportunities. Nevertheless, the pipeline presented can be also useful for the analysis of dynamic alterations of other biomolecules.

KEYWORDS:

AP-SWATH; Biological interpretation; Clustering analysis; Dynamic interactomics; Practical tutorial

PMID:
28433760
DOI:
10.1016/j.jprot.2017.04.011
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center