Computational Insight into Druggable Genome of Rothia mucilaginosa for Identification of Potential Drug Targets

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Date
2015
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The pathogenic organism Rothia mucilaginosa having the complete genome sequence. Detection of bacterial genes that are non-homologous to human genes, and are essential for the survival of the pathogen represents a promising means of identifying novel drug targets (Sakharkar et al., 2004). Many infectious diseases caused by this organism. The prolonged use of antibiotics over the years has transformed many organisms into resistant to multiple drugs (Georege and Umrania, 2011). So emergence of drug resistance of R. mucilaginosa has led to discover novel drug targets (Yadav and Pandey, 2013), that might facilitate the discovery of novel drugs in near future (Georege and Umrania, 2011). Whole genome sequence of the Rothia mucilaginosa DY_18 was analysed to identify potential drug targets. Total 1907 number of protein coding genes were studied from this organism. The DEG analysis was done to identify essential proteins to the organism. There were 685 sequences were identified as essential proteins to R. mucilaginosa. Through BLAST search 249 protein sequences were identified as non-homologous to human; so those proteins have less side effects to human. Again through Perl programming BLAST search was carried out against human gut flora microorganisms; there were 45 protein sequences were screened out as non- homologous to human gut flora. The KEGG pathway analysis was done to more validate the identified drug targets; through this pathway analysis 8 protein sequences were taken as novel drug targets against R. mucilaginosa based on metabolic pathways. Then to study about the intractome analysis, STRING was used, through which the interaction between the drugs targets were analysed clearly which might be more validate for more effective drug discovery against Rothia mucilaginosa. Therefore, the in silico analysis provides rapid and potential approach for identification of potential and novel drug targets.
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