Communication interception of human signal transduction pathways by human immunodeficiency Virus-1

Sivaraman Balakrishnan, Oznur Tastan, Jaime G. Carbonell, Judith Klein-Seetharaman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Signal transduction pathways are central to most biological processes. Diversion of such pathways is postulated to be central to the mechanism by which the Human Immunodeficiency Virus-1 (HIV) takes over the human cellular machinery. In this paper, we present an analysis of the interactions between HIV and human signal transduction pathways. We find that the majority of known human pathways are targeted through at least one HIV,human protein interaction (277 of the 453 pathways we considered). There are some pathways in which HIV interacts with disproportionately many proteins, targeting a single pathway at multiple positions. These numerous interactions are not just a function of the size of the pathways; other large pathways are not necessarily targeted to the same extent. Based on this analysis, we propose a novel rational drug design strategy as one of identifying possible "alternate" pathways. Activating or suppressing them may bypass HIV targeted pathways, thus exploiting redundancies in the human protein interaction network.

Original languageEnglish (US)
Title of host publication2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009 - Minneapolis, MN, United States
Duration: May 17 2009May 21 2009

Publication series

Name2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009

Conference

Conference2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009
Country/TerritoryUnited States
CityMinneapolis, MN
Period5/17/095/21/09

ASJC Scopus subject areas

  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

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