Analysis of signaling networks distributed over intracellular compartments based on protein-protein interactions

BMC Genomics

Research

Björn Sommer¹  Ralf Hofestädt¹  Olga Vasil'evna Popik²  Olga Vladimirovna Saik²  Evgeny Dmitrievich Petrovskiy²  Inna Nikolaevna Lavrik³  Vladimir Aleksandrovich Ivanisenko⁴ 

[1] Faculty of Technology, Bioinformatics Department, Bielefeld University, Bielefeld, Germany;The institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia;The institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia;Medical Faculty, Department Translational Inflammation Research, Otto von Guericke University Magdeburg, Magdeburg, Germany;The institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia;Novosibirsk State University, Novosibirsk, Russia;

关键词: Functional Classis;    Intracellular Compartment;    Reaction Efficiency;    Correlation Distance;    Boolean Model;   

DOI  :  10.1186/1471-2164-15-S12-S7

来源: Springer

【 摘 要 】

BackgroundBiological processes are usually distributed over various intracellular compartments. Proteins from diverse cellular compartments are often involved in similar signaling networks. However, the difference in the reaction rates between similar proteins among different compartments is usually quite high. We suggest that the estimation of frequency of intracompartmental as well as intercompartmental protein-protein interactions is an appropriate approach to predict the efficiency of a pathway.ResultsUsing data from the databases STRING, ANDSystem, IntAct and UniProt, a PPI frequency matrix of intra/inter-compartmental interactions efficiencies was constructed. This matrix included 15 human-specific cellular compartments. An approach for estimating pathway efficiency using the matrix of intra/inter-compartmental PPI frequency, based on analysis of reactions efficiencies distribution was suggested. An investigation of KEGG pathway efficiencies was conducted using the developed method. The clusterization and the ranking of KEGG pathways based on their efficiency were performed. "Amino acid metabolism" and "Genetic information processing" revealed the highest efficiencies among other functional classes of KEGG pathways. "Nervous system" and "Signaling molecules interaction" contained the most inefficient pathways. Statistically significant differences were found between efficiencies of KEGG and randomly-generated pathways. Based on these observations, the validity of this approach was discussed.ConclusionThe estimation of efficiency of signaling networks is a complicated task because of the need for the data on the kinetic reactions. However, the proposed method does not require such data and can be used for preliminary analysis of different protein networks.

【 授权许可】

Unknown   
© Popik et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.