Homology Modeling and Conformational Epitope Prediction of @entity26633 of Alkhumra XXXX .

@entity71298 @entity71297 @entity26633 @entity548
BACKGROUND: The aim of this study was to generate in silico 3D-structure of the @entity26633 of @entity71297 using homology modeling method to further predict its conformational epitopes and help other studies to investigate its structural features using the model. METHODS: A 3D-structure prediction was developed for the @entity26633 of Alkhumra @entity548 ( @entity71297 ), an emerging tick-borne flavivirus, based on a homology modeling method using M4T and Modweb servers, as the 3D-structure of the protein is not available yet. Modeled proteins were validated using Modfold 4 server and their accuracies were calculated based on their RSMDs. Having the 3D predicted model with high quality, conformational epitopes were predicted using DiscoTope 2.0. RESULTS: Model generated by M4T was more acceptable than the Modweb-generated model. The global score and P-value calculated by Modfold 4 ensured that a certifiable model was generated by @entity71298 , since its global score was almost near 1 which is the score for a high resolution X-ray crystallography structure. Furthermore, itsthe P-value was much lower than 0.001 which means that the model is completely acceptable. Having 0.46    rmsd, this model was shown to be highly accurate. Results from DiscoTope 2.0 showed 26 residues as epitopes, forming conformational epitopes of the modeled protein. CONCLUSION: The predicted model and epitopes for @entity26633 of @entity71297 can be used in several therapeutic and diagnostic approaches including peptide vaccine development, structure based drug design or diagnostic kit development in order to facilitate the time consuming experimental epitope mapping process.
