de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  The integrated analysis of metabolic and protein interaction networks reveals novel molecular organizing principles

Durek, P., & Walther, D. (2008). The integrated analysis of metabolic and protein interaction networks reveals novel molecular organizing principles. BMC Systems Biology, 2, 100. doi:10.1186/1752-0509-2-100.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0014-27D0-3 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0014-27D1-1
Genre: Journal Article

Files

show Files
hide Files
:
Durek-2008-The integrated analy.pdf (Any fulltext), 2MB
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Durek, P.1, Author              
Walther, D.1, Author              
Affiliations:
1BioinformaticsCIG, Infrastructure Groups and Service Units, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, escidoc:1753303              

Content

show
hide
Free keywords: scale-free networks saccharomyces-cerevisiae small-world macromolecular interactions computational analysis escherichia-coli complex networks enzyme-reactions yeast dehydrogenase
 Abstract: Background: The study of biological interaction networks is a central theme of systems biology. Here, we investigate the relationships between two distinct types of interaction networks: the metabolic pathway map and the protein-protein interaction network (PIN). It has long been established that successive enzymatic steps are often catalyzed by physically interacting proteins forming permanent or transient multi-enzymes complexes. Inspecting high-throughput PIN data, it was shown recently that, indeed, enzymes involved in successive reactions are generally more likely to interact than other protein pairs. In our study, we expanded this line of research to include comparisons of the underlying respective network topologies as well as to investigate whether the spatial organization of enzyme interactions correlates with metabolic efficiency. Results: Analyzing yeast data, we detected long-range correlations between shortest paths between proteins in both network types suggesting a mutual correspondence of both network architectures. We discovered that the organizing principles of physical interactions between metabolic enzymes differ from the general PIN of all proteins. While physical interactions between proteins are generally dissortative, enzyme interactions were observed to be assortative. Thus, enzymes frequently interact with other enzymes of similar rather than different degree. Enzymes carrying high flux loads are more likely to physically interact than enzymes with lower metabolic throughput. In particular, enzymes associated with catabolic pathways as well as enzymes involved in the biosynthesis of complex molecules were found to exhibit high degrees of physical clustering. Single proteins were identified that connect major components of the cellular metabolism and may thus be essential for the structural integrity of several biosynthetic systems. Conclusion: Our results reveal topological equivalences between the protein interaction network and the metabolic pathway network. Evolved protein interactions may contribute significantly towards increasing the efficiency of metabolic processes by permitting higher metabolic fluxes. Thus, our results shed further light on the unifying principles shaping the evolution of both the functional (metabolic) as well as the physical interaction network.

Details

show
hide
Language(s): eng - English
 Dates: 2008-11-252008
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: ISI: ISI:000262309400001
DOI: 10.1186/1752-0509-2-100
ISSN: 1752-0509 (Electronic) 1752-0509 (Linking)
URI: ://000262309400001 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2607255/pdf/1752-0509-2-100.pdf?tool=pmcentrez
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: BMC Systems Biology
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 2 Sequence Number: - Start / End Page: 100 Identifier: -