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Choke point analysis of metabolic pathways in E.histolytica: A computational approach for drug target identification

With the Entamoeba genome essentially complete, the organism can be studied from a whole genome standpoint. The understanding of cellular mechanisms and interactions between cellular components is instrumental to the development of new effective drugs and vaccines. Metabolic pathway analysis is beco...

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Detalles Bibliográficos
Autores principales: Singh, Shailza, Malik, Balwant Kishen, Sharma, Durlabh Kumar
Formato: Texto
Lenguaje:English
Publicado: Biomedical Informatics Publishing Group 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2174424/
https://www.ncbi.nlm.nih.gov/pubmed/18188424
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author Singh, Shailza
Malik, Balwant Kishen
Sharma, Durlabh Kumar
author_facet Singh, Shailza
Malik, Balwant Kishen
Sharma, Durlabh Kumar
author_sort Singh, Shailza
collection PubMed
description With the Entamoeba genome essentially complete, the organism can be studied from a whole genome standpoint. The understanding of cellular mechanisms and interactions between cellular components is instrumental to the development of new effective drugs and vaccines. Metabolic pathway analysis is becoming increasingly important for assessing inherent network properties in reconstructed biochemical reaction networks. Metabolic pathways illustrate how proteins work in concert to produce cellular compounds or to transmit information at different levels. Identification of drug targets in E. histolytica through metabolic pathway analysis promises to be a novel approach in this direction. This article focuses on the identification of drug targets by subjecting the Entamoeba genome to BLAST with the e-value inclusion threshold set to 0.005 and choke point analysis. A total of 86.9 percent of proposed drug targets with biological evidence are chokepoint reactions in Entamoeba genome database.
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spelling pubmed-21744242008-01-10 Choke point analysis of metabolic pathways in E.histolytica: A computational approach for drug target identification Singh, Shailza Malik, Balwant Kishen Sharma, Durlabh Kumar Bioinformation Hypothesis With the Entamoeba genome essentially complete, the organism can be studied from a whole genome standpoint. The understanding of cellular mechanisms and interactions between cellular components is instrumental to the development of new effective drugs and vaccines. Metabolic pathway analysis is becoming increasingly important for assessing inherent network properties in reconstructed biochemical reaction networks. Metabolic pathways illustrate how proteins work in concert to produce cellular compounds or to transmit information at different levels. Identification of drug targets in E. histolytica through metabolic pathway analysis promises to be a novel approach in this direction. This article focuses on the identification of drug targets by subjecting the Entamoeba genome to BLAST with the e-value inclusion threshold set to 0.005 and choke point analysis. A total of 86.9 percent of proposed drug targets with biological evidence are chokepoint reactions in Entamoeba genome database. Biomedical Informatics Publishing Group 2007-10-15 /pmc/articles/PMC2174424/ /pubmed/18188424 Text en © 2007 Biomedical Informatics Publishing Group This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.
spellingShingle Hypothesis
Singh, Shailza
Malik, Balwant Kishen
Sharma, Durlabh Kumar
Choke point analysis of metabolic pathways in E.histolytica: A computational approach for drug target identification
title Choke point analysis of metabolic pathways in E.histolytica: A computational approach for drug target identification
title_full Choke point analysis of metabolic pathways in E.histolytica: A computational approach for drug target identification
title_fullStr Choke point analysis of metabolic pathways in E.histolytica: A computational approach for drug target identification
title_full_unstemmed Choke point analysis of metabolic pathways in E.histolytica: A computational approach for drug target identification
title_short Choke point analysis of metabolic pathways in E.histolytica: A computational approach for drug target identification
title_sort choke point analysis of metabolic pathways in e.histolytica: a computational approach for drug target identification
topic Hypothesis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2174424/
https://www.ncbi.nlm.nih.gov/pubmed/18188424
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AT malikbalwantkishen chokepointanalysisofmetabolicpathwaysinehistolyticaacomputationalapproachfordrugtargetidentification
AT sharmadurlabhkumar chokepointanalysisofmetabolicpathwaysinehistolyticaacomputationalapproachfordrugtargetidentification