In Silico Approach of Structure Prediction and Functional Characterization of Zaire Ebola (Ebov) and Identification of Binding Site for Drug Development
Keywords:Zaire ebola, EBOV, Computational Tools, Active site, Mutation Point.
Zaire ebolavirus (EBOV) is one of the dangerous and a negative-stranded ssRNA virus. EBOV is a zoonotic pathogen that causes severe hemorrhagic fever in humans. Nowadays epidemic outbreak caused by EBOV is incurable with present technologies; thus figure out as a major health risk which needs enhanced surveillance. The study was conducted with seven proteins of Zaire ebola (EBOV) and gene sequences are available in NCBI database. The homology modeling was done by SWISS-MODEL, Phyre2 and HHpred. The obtained model was verified with structure validation programs such as PROCHECK, Verify3D and ERRAT. PROCHECK analysis of seven proteins showed that 85-96.6% of the residues are in the most favored region, the verify 3D value of 80-100% indicates that constructed model is good and ERRAT value of 87.442-100% indicates that overall good quality factor. In this study, we also reported phylogenic relationship, physico-chemical characteristics, secondary structure,3-D structure. Moreover, active sites were identified by CASTp suggests that these proteins can be utilized as a potential drug target. Furthermore, the initial findings were reinforced by the results from I-Mutant and mCSM as these tools predicted significant and functional instability of the mutated vp35 protein.
Int J Appl Sci Biotechnol, Vol 4(1): 92-103