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ISSN: 0974-7230

Journal of Computer Science & Systems Biology
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Research Article

In Silico Pathway Analysis Predicts Metabolites that are Potential Antimicrobial Targets

Malabika Sarker1, Sidharth Chopra2, Kristien Mortelmans2, Krishna Kodukula3, Carolyn Talcott1 and Amit K. Galande3*

1Computer Science Laboratory, SRI International, Menlo Park, CA 94025

2Center for Infectious Disease and Biodefense Research, SRI International, Menlo Park, CA 94025

3Center for Advanced Drug Research, SRI International, Harrisonburg, Virginia 22802, USA

*Corresponding Author:
Dr. Amit K. Galande
Center for Advanced Drug Research
SRI International, Harrisonburg, Virginia 22802, USA
Tel: (540) 438 6621
Fax: (540) 568 5758
E-mail: [email protected]

Received date: April 04, 2011; Accepted date: April 20, 2011; Published date: April 25, 2011

Citation: Sarker M, Chopra S, Mortelmans K, Kodukula K, Talcott C, et al. (2011) In Silico Pathway Analysis Predicts Metabolites that are Potential Antimicrobial Targets. J Comput Sci Syst Biol 4:021-026. doi:10.4172/jcsb.1000071

Copyright: © 2011 Sarker M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

Antibiotic discovery aimed at conventional targets such as proteins and nucleic acids faces challenges from mutations and antibiotic resistance. Small molecule metabolites, however, can be considered resistant to change, as they do not undergo rapid mutations. Developing analogs or scavengers of essential microbial metabolites as antibiotics is a promising strategy that can delay drug resistance. The objective of this work was to identify microbial metabolites that are most suitable targets for antimicrobial discovery. We performed extensive literature mining and systems level pathway analysis to identify bacterial metabolites that fulfill the criteria for drug targets. The BioCyc interactive metabolic pathway maps and Pathway Tools software were used to corroborate our finding. We identified ten metabolites as potential candidates for developing novel antibiotics. These metabolites are Lipid II, meso-diaminopimelate, pantothenate, shikimate, biotin, L-aspartyl-4-phosphate, dTDP-?-L-rhamnose, UDP-Dgalacto- 1,4-furanose, des-N-acetyl mycothiol, and Siroheme. The article describes the selection criteria, analysis of metabolic pathways, and the potential role of each of the ten metabolites in therapeutic intervention as broadspectrum antibiotics with emphasis on M. tuberculosis. Our study revealed previously unexplored targets along with metabolites that are well established in antibiotic discovery. Identification of established metabolites strengthen our analyses while the newly discovered metabolites could lead to novel antimicrobials.

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