Abstract

BackgroundFunctional modules in protein-protein interaction networks (PPIN) are defined by maximal sets of functionally associated proteins and are vital to understanding cellular mechanisms and identifying disease associated proteins. Topological modules of the human proteome have been shown to be related to functional modules of PPIN. However, the effects of the weights of interactions between protein pairs and the integration of physical (direct) interactions with functional (indirect expression-based) interactions have not been investigated in the detection of functional modules of the human proteome.ResultsWe investigated functional homogeneity and specificity of topological modules of the human proteome and validated them with known biological and disease pathways. Specifically, we determined the effects on functional homogeneity and heterogeneity of topological modules (i) with both physical and functional protein-protein interactions; and (ii) with incorporation of functional similarities between proteins as weights of interactions. With functional enrichment analyses and a novel measure for functional specificity, we evaluated functional relevance and specificity of topological modules of the human proteome.ConclusionsThe topological modules ranked using specificity scores show high enrichment with gene sets of known functions. Physical interactions in PPIN contribute to high specificity of the topological modules of the human proteome whereas functional interactions contribute to high homogeneity of the modules. Weighted networks result in more number of topological modules but did not affect their functional propensity. Modules of human proteome are more homogeneous for molecular functions than biological processes.

Highlights

  • Functional modules in protein-protein interaction networks (PPIN) are defined by maximal sets of functionally associated proteins and are vital to understanding cellular mechanisms and identifying disease associated proteins

  • Protein-protein interaction networks (PPIN) like most biological networks are believed to be modular in nature [4, 9, 10] and detecting functional modules of PPIN are vital for understanding gene-function associations and designing therapeutics

  • Here we investigate the role of edge weights incorporated from gene functional similarities in the modular detection of PPIN

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Summary

Introduction

Functional modules in protein-protein interaction networks (PPIN) are defined by maximal sets of functionally associated proteins and are vital to understanding cellular mechanisms and identifying disease associated proteins. Biomolecules (genes, RNA, proteins, metabolites) interact with each other and environmental factors in order to accomplish various biological processes. Representing these interactions as biological networks (metabolic, protein-protein interactions, gene regulatory, co-expression) and their analyses provide insights in finding genes associated with cellular. Protein-protein interaction networks (PPIN) like most biological networks are believed to be modular in nature [4, 9, 10] and detecting functional modules of PPIN are vital for understanding gene-function associations and designing therapeutics. Computational methods accurately inferring functional and disease modules of the human proteome would be of paramount importance for studying cellular and disease mechanisms

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