Functional, structural and epitopic prediction of hypothetical proteins of Mycobacterium tuberculosis H37Rv: An in silico approach for prioritizing the targets

The global control of tuberculosis (TB) remains a great challenge from the standpoint of diagnosis, detection of drug resistance, and treatment. Major serodiagnostic limitations include low sensitivity and high cost in detecting TB. On the other hand, treatment measures are often hindered by low efficacies of commonly used drugs and resistance developed by the bacteria. Hence, there is a need to look into newer diagnostic and therapeutic targets. The proteome information available suggests that among the 3906 proteins in Mycobacterium tuberculosis H37Rv, about quarter remain classified as hypothetical uncharacterized set. This study involves a combination of a number of bioinformatics tools to analyze those hypothetical proteins (HPs). An entire set of 999 proteins was primarily screened for protein sequences having conserved domains with high confidence using a combination of the latest versions of protein family databases. Subsequently, 98 of such potential target proteins were extensively analyzed by means of physicochemical characteristics, protein-protein interaction, sub-cellular localization, structural similarity and functional classification. Next, we predicted antigenic proteins from the entire set and identified B and T cell epitopes of these proteins in M. tuberculosis H37Rv. We predicted the function of these HPs belong to various classes of proteins such as enzymes, transporters, receptors, structural proteins, transcription regulators and other proteins. However, the structural similarity prediction of the annotated proteins substantiated the functional classification of those proteins. Consequently, based on higher antigenicity score and sub-cellular localization, we choose two (NP_216420.1, NP_216903.1) of the antigenic proteins to exemplify B and T cell epitope prediction approach. Finally we found 15 epitopes those located partially or fully in the linear epitope region. We found 21 conformational epitopes by using Ellipro server as well. In silico methodology used in this study and the data thus generated for HPs of M. tuberculosis H37Rv may facilitate swift experimental identification of potential serodiagnostic and therapeutic targets for treatment and control.