Harnessing subtractive genomics for drug target identification in Streptococcus agalactiae serotype v (atcc baa-611 / 2603 v/r) strain: An in-silico approach.

Abstract

Developing a therapeutic target for bacterial disease is challenging. In silico subtractive genomics methodology offer a promising alternative to traditional drug discovery methods. Streptococcus agalactiae infections depend on two crucial criteria: drug-resistance and the existence of virulence factors. It is essential to underline that S. agalactiae strains have emerged to be resistant to several drugs. Hence, there is a need for research on novel drugs and techniques that are potent, economical, productive, and dependable to combat S. agalactiae infections. In this study advanced computational techniques were exploited to examine potential druggable targets exclusive to this pathogen. Our study uncovered 200 non-homologous proteins in S. agalactiae serotype V (Strain ATCC BAA-611/ 2603 V/R) and identified 68 essential proteins indispensable for the bacterium's survival. Therefore, these 68 proteins are potential targets for drug development. Subcellular localization analysis unveiled that the pathogen's cytoplasmic membrane contained essential proteins among these vital non-homologous proteins. On the other hand, based on virulent protein predictions, six proteins were seen to be virulent. Among these, we prioritized two proteins (Sensor protein LytS and Galactosyl transferase CpsE which are exclusively found in S. agalactiae) as potential druggable targets and selected them for further structural investigation. The proteins chosen could serve as a foundation for the identification of a promising therapeutic compound that has the potential to neutralize these enzymatic proteins, thereby contributing to the reduction of risks linked to the drug-resistant S. agalactiae.