Journal of Bioinformatics, Proteomics and Imaging Analysis
In silico putative drug target identification in Enterobacter cloacae and homology modelling of a candidate drug target
In Silico Putative Drug Target Identification in Enterobacter Cloacae and Homology Modelling of a Candidate Drug Target
Yadav, P.K., et al. In Silico Putative Drug Target Identification in Enterobacter Cloacae and Homology Modelling of aCandidate Drug Target (2016) Bioinfo Proteom Img Anal 2(1): 65-70.
Yadav, P.K., et al. In Silico Putative Drug Target Identification in Enterobacter Cloacae and Homology Modelling of a Candidate Drug Target (2016) J Bioinfo Proteomics Rev 2(1): 1- 6.
© 2016 Yadav, P.K. This is an Open access article distributed under the terms of Creative Commons Attribution 4.0 International License.
KeywordsEnterobacter cloacae, KEGG, metabolic pathways, drug targets, homology modelling
Enterobacter cloacae is a clinically significant Gram-negative, facultatively-anaerobic, rod-shaped bacterium, which has emerged as a prevalent nosocomial pathogen due to high level resistance to antimicrobial drugs. The availability of complete genome sequence of E. cloacae has paved the novel way to identify the new drug targets. In the present work comparative analysis of the metabolic pathways of the pathogen and human host was performed to identify the novel targets present in pathogen but absent in host. All enzymes involved in the metabolic pathways of E. cloacae were searched against the proteome of Homo sapiens using the BLASTp program using certain parametes. Approximately 44 unique non-homologous putative drug targets were identified. Among all these targets, 22 coding genes for putative targets were identified as essential in the DEG database for survival of the pathogen. After extensive literature survey, 8 targets were identified as potential drug. Among these targets UDP-N-acetylmuramate-L-alanine ligase (MurC) was chosen as candidate drug target for further study, because it was involved in many metabolic pathways of E. cloacae. The physico-chemical properties of the MurC protein were analyzed using the Protparam tool, and it was found the protein is stable in nature. The 3D structure of MurC enzyme was predicted using SWISS-MODEL and HHPred server respectively. Subsequently, all the predicted models were evaluated using the SAVES server. The best quality model was predicted by HHPred server which was having quality factor of 90.64, and approximately 90% of residues were falling in core regions of Ramachandran plot. The quality of the model was further validated by ProSA server. In future, the 3D structure of MurC in Enterobacter cloacae might be exploited for the discovery of novel inhibitors using structure-based drug design strategy that could potentially inhibit the pathogen.