Exploring the genomic potential of Kytococcus schroeteri for antibacterial metabolites against multi-drug resistant Mycobacterium tuberculosis

The versatile bacterium Kytococcus schroeteri is known for producing putative secondary metabolites. These include antimicrobials and other therapeutically significant compounds. The emergence of antibiotic-resistant pathogens has necessitated the exploration of possible sources for novel drug candidates. This study focuses on the genome mining of Kytococcus schroeteri to explore its secondary metabolites through biosynthetic gene clusters. It analyzes their drug-like properties through in-silico methods and evaluates their potential as antimicrobial agents. Eight biosynthetic gene clusters were identified in two strains (H01 and UMB1298) of this bacterium. Among the unique 49 metabolites from these clusters, 13 metabolites were selected according to the Lipinski rule of five. Physiochemical properties, pharmacokinetic analysis, toxicity profiles, and human target predictions of these metabolites were performed, and they were examined for crucial interactions with M. tuberculosis's RpfB protein, the causative agent of latent tuberculosis. All metabolites were predicted to be non-toxic and did not inhibit any human proteins. Several metabolites, including a subset of brasilanes, exhibited both low acute toxicity and promising interactions with GLU292, the critical residue of the RpfB protein. The interaction affinity of the ligands with RpfB was validated by subjecting one of the complexes to a 100 ns MD simulation. The RMSD, RMSF, and binding energy calculations indicated a stable interaction of the ligand with the receptor protein, which raised the possibility of novel drugs to combat antibiotic resistance. The putative metabolites identified in this study not only exhibit molecular properties but also possess characteristics that support physiological compatibility. It also heightens their potential effectiveness as therapeutic antibacterial alternates. The experimental validation of our computational results may open an avenue to explore the potential of K. schroeteri for producing novel compounds to combat the antibiotic resistance in M. tuberculosis.