Computational Analysis, in silico Functional Annotation and Expression of Recombinant mycobacterium, PE_PGRS Protein Biomarkers

Background Over the years, there have been many advances made within the treatment and diagnosis of Mycobacterium Tuberculosis ( Mtb ). In recent times, the rise of drug resistance has led to higher mortality rates specifically in poorer countries. There is an urgent need for novel treatment regimens to work against Mtb . A gene family, found in Mtb , PE_PGRS proteins shows potential as a drug target in its life cycle; to prevent the activation of latent Mtb to active Mtb . In silico functional annotations of these proteins are cost-effective and avoid wasting effort on a protein with no potential. Method Previous studies indicated that the PE_PGRS showed potential for further research. The protein biomarkers which showed the most promise was identified as PE_PGRS17, PE_PGRS31, PE_PGRS50 and PEPGRS54. The sequences of these proteins were searched on the Mycobrowser software. Results were designed by entering these sequences into various computational algorithms. PE_PGRS17 showed characteristics of a potential vaccine candidate. Considering this result, expression profiling and purification was conducted on the recombinant PE_PGRS17 Mtb protein biomarker. Results and Discussion The results were calculated using various online software algorithms. Many characterizations and other aspects were predicted to understand the stability, localization, and function of these proteins. All the proteins are estimated to produce an immune response or be involved in the process of immunity. The expression condition of the recombinant PE_PGRS17 was optimised, and purification strategy achieved using E.coli as a host cell. These findings make these proteins, specifically PE_PGRS17, popular for further scientific study. Conclusion The predicted structures, protein-protein interaction and antigenic properties of the proteins estimate whether the protein can be used for further studies specifically as drug/vaccine targets. Ultimately PE_PGRS17 is seen as the most stable according to its structure and it holds more promise as a key factor to tuberculosis studies.