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Copyright © 2015 | AIZEON publishers | All rights reserved

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International Journal of Computational Bioinformatics and In Silico Modeling
2015: Volume-4 Issue-1
ISSN: 2320-0634

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ABSTRACT   REFERENCES  
International Journal of Computational Bioinformatics and In Silico Modeling 4(1) 2015: 585-591

In silico identification of putative drug targets in methicillin resistant Staphylococcus aureus: a subtractive genomic approach



Ononamadu Chimaobi James1*, Umeoguaju Uchenna Francis2, Owolarafe Tajudeen Alowonle1, Udedi Stanley Chukwudi2, Barau Muhammad Mustapha1 and Ofoegbu Chukwudi Jude3

1 Dept of Biochemistry and Forensic Science, Nigeria Police Academy, Wudil, Kano State, Nigeria
2 Dept of Applied Biochemistry, NnamdiAzikiwe University, Awka, Anambra State, Nigeria
3 Biochemisty uint of the Dept of Science Laboratory Technology, Federal University of Technology. Owerri, Imo State, Nigeria

* Corresponding Author

ABSTRACT

Staphylococcus aureus is a gram positive, coagulase positive coccus in the family staphyloccocaceae. It is an opportunistic organism that has emerged as one of the predominant pathogens in community and healthcare-associated infections with limited and less effective options for treatment in the face of a rising trend in the emergence of resistant strains. This fact has necessitated the search for alternative targets for development of new drugs. In this present study, a subtractive genomic (proteome) approach was used to identify potential drug targets in methicillin resistant Staphylococcus aureus using strain 252 (MSRA252). The complete  proteome  of MSRA 252  obtained from Uniprot database was subjected to  CD-hit  suite for clustering;  NCBI BlastP suite against the human proteome to exclude  homologous proteins; and sequence homology  with Database of Essential Genes(DEG) to determine the indispensability of the proteins for the bacteria survival.  The essential proteins were further analyzed to predict the metabolic pathways they were involved in using KEGG automatic annotation server (KAAS) and their subcellular locations using, Uniprot and PsortB suite subsequently. The sequence sorting, segregation and formatting was carried out using UFS Sequence Analysis Application after each successive step. The study identified 291 essential non homologous proteins to human out of 2640. Further analysis with KAAS revealed that 114 (33 predicted membrane-associated) of the essential non homologous proteins were involved in different metabolic pathways in the organism and 60 of these were implicated in pathways unique to the bacteria relative to human (host). The study revealed a number of putative, essential non homologous protein candidates that could be further explored for the development of alternative treatments and vaccines for methicillin resistant Staphylococcus aureus infections.

 


Copyright © 2015 | AIZEON publishers | All rights reserved

 

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Citation: Ononamadu Chimaobi James et al. (2015). In silico identification of putative drug targets in methicillin resistant Staphylococcus aureus: a subtractive genomic approach. Int J Comput Bioinfo In Silico Model 4(1): 585-591

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