Understanding the structural basis of the binding specificity of c-di-AMP to M. smegmatis RecA using computational biology approach.

Mycobacterium tuberculosis RecA (MtRecA), a protein involved in DNA repair, homologous recombination and SOS pathway, contributes to the development of multidrug resistance. ATP binding-site in RecA has been a drug target to disable RecA dependent DNA repair. For the first time, experiments have shown the existence and binding of c-di-AMP to a novel allosteric site in the C-terminal-Domain (CTD) of Mycobacterium smegmatis RecA (MsRecA), a close homolog of MtRecA. In addition, it was observed that the c-di-AMP was not binding to Escherichia coli RecA (EcRecA). This article analyses the possible interactions of the three RecA homologs with the various c-di-AMP conformations to gain insights into the structural basis of the natural preference of c-di-AMP to MsRecA and not to EcRecA, using the structural biology tools. The comparative analysis, based on amino acid composition, homology, motifs, residue types, docking, molecular dynamics simulations and binding free energy calculations, indeed, conclusively indicates strong binding of c-di-AMP to MsRecA. Having very similar results as MsRecA, it is highly plausible for c-di-AMP to strongly bind MtRecA as well. These insights from the in-silico studies adds a new therapeutic approach against TB through design and development of novel allosteric inhibitors for the first time against MtRecA.Communicated by Ramaswamy H. Sarma.

An in silico approach to study the role of epitope order in the multi-epitope-based peptide (MEBP) vaccine design.

With different countries facing multiple waves, with some SARS-CoV-2 variants more deadly and virulent, the COVID-19 pandemic is becoming more dangerous by the day and the world is facing an even more dreadful extended pandemic with exponential positive cases and increasing death rates. There is an urgent need for more efficient and faster methods of vaccine development against SARS-CoV-2. Compared to experimental protocols, the opportunities to innovate are very high in immunoinformatics/in silico approaches, especially with the recent adoption of structural bioinformatics in peptide vaccine design. In recent times, multi-epitope-based peptide vaccine candidates (MEBPVCs) have shown extraordinarily high humoral and cellular responses to immunization. Most of the publications claim that respective reported MEBPVC(s) assembled using a set of in silico predicted epitopes, to be the computationally validated potent vaccine candidate(s) ready for experimental validation. However, in this article, for a given set of predicted epitopes, it is shown that the published MEBPVC is one among the many possible variants and there is high likelihood of finding more potent MEBPVCs than the published candidates. To test the same, a methodology is developed where novel MEBP variants are derived by changing the epitope order of the published MEBPVC. Further, to overcome the limitations of current qualitative methods of assessment of MEBPVC, to enable quantitative comparison and ranking for the discovery of more potent MEBPVCs, novel predictors, Percent Epitope Accessibility (PEA), Receptor specific MEBP vaccine potency (RMVP), MEBP vaccine potency (MVP) are introduced. The MEBP variants indeed showed varied MVP scores indicating varied immunogenicity. Further, the MEBP variants with IDs, SPVC_446 and SPVC_537, had the highest MVP scores indicating these variants to be more potent MEBPVCs than the published MEBPVC and hence should be preferred candidates for immediate experimental testing and validation. The method enables quicker selection and high throughput experimental validation of vaccine candidates. This study also opens the opportunity to develop new software tools for designing more potent MEBPVCs in less time.