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Comparative Protein Interaction Network Analysis Identifies Shared and Distinct Functions for the Human ROCO Proteins

Tomkins, JE; Dihanich, S; Beilina, A; Ferrari, R; Ilacqua, N; Cookson, MR; Lewis, PA; (2018) Comparative Protein Interaction Network Analysis Identifies Shared and Distinct Functions for the Human ROCO Proteins. Proteomics , 18 (10) , Article 1700444. 10.1002/pmic.201700444. Green open access

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Abstract

Signal transduction cascades governed by kinases and GTPases are a critical component of the command and control of cellular processes, with the precise outcome partly determined by direct protein-protein interactions (PPIs). Here, we use the human ROCO proteins as a model for investigating PPI signalling events - taking advantage of the unique dual kinase/GTPase activities and scaffolding properties of these multidomain proteins. We report PPI networks that encompasses the human ROCO proteins, developed using two complementary approaches. First, using our recently developed weighted PPI network analysis (WPPINA) pipeline, a confidence-weighted overview of validated ROCO protein interactors was obtained from peer-reviewed literature. Second, novel ROCO PPIs were assessed experimentally via protein microarray screens. We compared the networks derived from these orthologous approaches to identify common elements within the ROCO protein interactome; functional enrichment analysis of this common core of the network identified stress response and cell projection organisation as shared functions within this protein family. Despite the presence of these commonalities, our results suggest that many unique interactors and therefore some specialised cellular roles have evolved for different members of the ROCO proteins. Overall, this multi-approach strategy to increase the resolution of protein interaction networks represents a prototype for the utility of PPI data integration in understanding signalling biology. This article is protected by copyright. All rights reserved.

Type: Article
Title: Comparative Protein Interaction Network Analysis Identifies Shared and Distinct Functions for the Human ROCO Proteins
Location: Germany
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/pmic.201700444
Publisher version: https://doi.org/10.1002/pmic.201700444
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Keywords: BioGRID, Bioinformatics, Data integration, Data mining, Innate, IntAct, MINT, Protein microarray, ROCO proteins
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy > Pharmacology
URI: https://discovery.ucl.ac.uk/id/eprint/10046223
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