Exploring and targeting potential druggable antimicrobial resistance targets ArgS, SecY and MurA in Staphylococcus sciuri with TCM inhibitors through subtractive genomics strategy

Abstract

Abstract Staphylococcus sciuri (also currently Mammaliicoccus sciuri) are anaerobic facultative and non-motile bacteria that causes significant human pathogenesis such as endocarditis, wound infections, peritonitis, UTI and septic shock. Some methicillin-resistant S. sciuri (MRSS) also infects animals that include healthy broilers, cattle, dogs and pigs. The emergence of MRSS strains thereby poses a serious health threat and thrives the scientific community towards novel treatment options. Herein, we investigated the druggable genome of S. sciuri by employing subtractive genomics that resulted in 7 genes/proteins where only 3 of them were predicted as final targets. Further mining the literature showed that the ArgS (WP_058610923), SecY (WP_058611897) and MurA (WP_058612677) are involved in multi-drug resistance phenomenon. The 3D protein homology models were built and validated, followed by screening against a Traditional Chinese Medicine library (n = 36,043 compounds). The molecular docking and simulation studies revealed the physicochemical stability parameters of the docked TCM inhibitors in the druggable cavities of each protein targets by identifying their druggability potential and maximum Hydrogen bonding interactions. The RMSD graph showed fluctuations due to structural changes in the helix-coil-helix and beta-turn-beta changes at specific points. Additionally, the transitional changes in protein targets due to “relational dynamics” significantly impact the receptor-ligand binding mechanism. It is assumed that such findings might facilitate researchers to robustly discover and develop effective therapeutics against S. sciuri alongside other enteric infections.