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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...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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Biomedical Informatics Publishing Group
2007
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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. |
format | Text |
id | pubmed-2174424 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Biomedical Informatics Publishing Group |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT singhshailza chokepointanalysisofmetabolicpathwaysinehistolyticaacomputationalapproachfordrugtargetidentification AT malikbalwantkishen chokepointanalysisofmetabolicpathwaysinehistolyticaacomputationalapproachfordrugtargetidentification AT sharmadurlabhkumar chokepointanalysisofmetabolicpathwaysinehistolyticaacomputationalapproachfordrugtargetidentification |