Title

Authors

Affiliation

¹Department of Computational Biology & Bioinformatics, JSBB, SHIATS (DU), Allahabad-211007, India; ²Department of Computer Science & IT, SSET, SHIATS (DU), Allahabad-211007, India; ³Department of Molecular & Cellular Engineering, JSBB, SHIATS (DU), Allahabad-211007, India.

Email

pramod.yadav@shiats.edu.in; *Corresponding author

Article Type

Hypothesis

Date

Received June 24, 2012; Accepted July 05, 2012; Published July 21, 2012

The emergence of multidrug-resistant strain of community-acquired methicillin resistant Staphylococcus aureus (CA-MRSA) strain has highlighted the urgent need for the alternative and effective therapeutic approach to combat the menace of this nosocomial pathogen. In the present work novel potential therapeutic drug targets have been identified through the metabolic pathways analysis. All the gene products involved in different metabolic pathways of CA-MRSA in KEGG database were searched against the proteome of Homo sapiens using the BLASTp program and the threshold of E-value was set to as 0.001. After database searching, 152 putative targets were identified. Among all 152 putative targets, 39 genes encoding for putative targets were identified as the essential genes from the DEG database which are indispensable for the survival of CA-MRSA. After extensive literature review, 7 targets were identified as potential therapeutic drug target. These targets are Fructose-bisphosphate aldolase, Phosphoglyceromutase, Purine nucleoside phosphorylase, Uridylate kinase, Tryptophan synthase subunit beta, Acetate kinase and UDP-N-acetylglucosamine 1-carboxyvinyltransferase. Except Uridylate kinase all the identified targets were involved in more than one metabolic pathways of CA-MRSA which underlines the importance of drug targets. These potential therapeutic drug targets can be exploited for the discovery of novel inhibitors for CA-MRSA using the structure based drug design (SBDD) strategy.

Keywords

Drug target, metabolic pathways, CA-MRSA, KEGG, DEG

Citation

Yadav et al. Bioinformation 8(14): 664-672 (2012)
 

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.