Cargando…

A quantitative approach to study indirect effects among disease proteins in the human protein interaction network

BACKGROUND: Systems biology makes it possible to study larger and more intricate systems than before, so it is now possible to look at the molecular basis of several diseases in parallel. Analyzing the interaction network of proteins in the cell can be the key to understand how complex processes lea...

Descripción completa

Detalles Bibliográficos
Autores principales: Nguyen, Thanh-Phuong, Jordán, Ferenc
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2924296/
https://www.ncbi.nlm.nih.gov/pubmed/20670417
http://dx.doi.org/10.1186/1752-0509-4-103
_version_ 1782185566125686784
author Nguyen, Thanh-Phuong
Jordán, Ferenc
author_facet Nguyen, Thanh-Phuong
Jordán, Ferenc
author_sort Nguyen, Thanh-Phuong
collection PubMed
description BACKGROUND: Systems biology makes it possible to study larger and more intricate systems than before, so it is now possible to look at the molecular basis of several diseases in parallel. Analyzing the interaction network of proteins in the cell can be the key to understand how complex processes lead to diseases. Novel tools in network analysis provide the possibility to quantify the key interacting proteins in large networks as well as proteins that connect them. Here we suggest a new method to study the relationships between topology and functionality of the protein-protein interaction network, by identifying key mediator proteins possibly maintaining indirect relationships among proteins causing various diseases. RESULTS: Based on the i2d and OMIM databases, we have constructed (i) a network of proteins causing five selected diseases (DP, disease proteins) plus their interacting partners (IP, non-disease proteins), the DPIP network and (ii) a protein network showing only these IPs and their interactions, the IP network. The five investigated diseases were (1) various cancers, (2) heart diseases, (3) obesity, (4) diabetes and (5) autism. We have quantified the number and strength of IP-mediated indirect effects between the five groups of disease proteins and hypothetically identified the most important mediator proteins linking heart disease to obesity or diabetes in the IP network. The results present the relationship between mediator role and centrality, as well as between mediator role and functional properties of these proteins. CONCLUSIONS: We show that a protein which plays an important indirect mediator role between two diseases is not necessarily a hub in the PPI network. This may suggest that, even if hub proteins and disease proteins are trivially of great interest, mediators may also deserve more attention, especially if disease-disease associations are to be understood. Identifying the hubs may not be sufficient to understand particular pathways. We have found that the mediators between heart diseases and obesity, as well as heart diseases and diabetes are of relatively high functional importance in the cell. The mediator proteins suggested here should be experimentally tested as products of hypothetical disease-related proteins.
format Text
id pubmed-2924296
institution National Center for Biotechnology Information
language English
publishDate 2010
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-29242962010-08-20 A quantitative approach to study indirect effects among disease proteins in the human protein interaction network Nguyen, Thanh-Phuong Jordán, Ferenc BMC Syst Biol Methodology Article BACKGROUND: Systems biology makes it possible to study larger and more intricate systems than before, so it is now possible to look at the molecular basis of several diseases in parallel. Analyzing the interaction network of proteins in the cell can be the key to understand how complex processes lead to diseases. Novel tools in network analysis provide the possibility to quantify the key interacting proteins in large networks as well as proteins that connect them. Here we suggest a new method to study the relationships between topology and functionality of the protein-protein interaction network, by identifying key mediator proteins possibly maintaining indirect relationships among proteins causing various diseases. RESULTS: Based on the i2d and OMIM databases, we have constructed (i) a network of proteins causing five selected diseases (DP, disease proteins) plus their interacting partners (IP, non-disease proteins), the DPIP network and (ii) a protein network showing only these IPs and their interactions, the IP network. The five investigated diseases were (1) various cancers, (2) heart diseases, (3) obesity, (4) diabetes and (5) autism. We have quantified the number and strength of IP-mediated indirect effects between the five groups of disease proteins and hypothetically identified the most important mediator proteins linking heart disease to obesity or diabetes in the IP network. The results present the relationship between mediator role and centrality, as well as between mediator role and functional properties of these proteins. CONCLUSIONS: We show that a protein which plays an important indirect mediator role between two diseases is not necessarily a hub in the PPI network. This may suggest that, even if hub proteins and disease proteins are trivially of great interest, mediators may also deserve more attention, especially if disease-disease associations are to be understood. Identifying the hubs may not be sufficient to understand particular pathways. We have found that the mediators between heart diseases and obesity, as well as heart diseases and diabetes are of relatively high functional importance in the cell. The mediator proteins suggested here should be experimentally tested as products of hypothetical disease-related proteins. BioMed Central 2010-07-29 /pmc/articles/PMC2924296/ /pubmed/20670417 http://dx.doi.org/10.1186/1752-0509-4-103 Text en Copyright ©2010 Nguyen and Jordán; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Nguyen, Thanh-Phuong
Jordán, Ferenc
A quantitative approach to study indirect effects among disease proteins in the human protein interaction network
title A quantitative approach to study indirect effects among disease proteins in the human protein interaction network
title_full A quantitative approach to study indirect effects among disease proteins in the human protein interaction network
title_fullStr A quantitative approach to study indirect effects among disease proteins in the human protein interaction network
title_full_unstemmed A quantitative approach to study indirect effects among disease proteins in the human protein interaction network
title_short A quantitative approach to study indirect effects among disease proteins in the human protein interaction network
title_sort quantitative approach to study indirect effects among disease proteins in the human protein interaction network
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2924296/
https://www.ncbi.nlm.nih.gov/pubmed/20670417
http://dx.doi.org/10.1186/1752-0509-4-103
work_keys_str_mv AT nguyenthanhphuong aquantitativeapproachtostudyindirecteffectsamongdiseaseproteinsinthehumanproteininteractionnetwork
AT jordanferenc aquantitativeapproachtostudyindirecteffectsamongdiseaseproteinsinthehumanproteininteractionnetwork
AT nguyenthanhphuong quantitativeapproachtostudyindirecteffectsamongdiseaseproteinsinthehumanproteininteractionnetwork
AT jordanferenc quantitativeapproachtostudyindirecteffectsamongdiseaseproteinsinthehumanproteininteractionnetwork