A Computational Quest for Finding Novel Drug Targets against Mycobacterium tuberculosis

Tuberculosis (TB), caused by drug-resistant Mycobacterium tuberculosis, remains a formidable global health challenge, necessitating the identification of effective treatment targets. This prospective study aims to utilize computational-based research employing subtractive genomic techniques to identify potential targets against Mycobacterium tuberculosis. This study seeks to discover unique genes crucial for Mycobacterium tuberculosis survival and virulence. Unlike previous studies that focus primarily on essential gene identification, this research integrates subtractive genomics with metabolic pathway analysis, structural modeling, and Protein-Protein Interaction assessments to enhance target validation. Employing powerful computational methods and bioinformatics tools, the study aims to elucidate the roles of these genes in bacterial physiology and disease. The anticipated outcomes include the identification of critical pathways associated with bacterial adaptability, metabolic processes, and cell wall construction that may serve as potential treatment targets. Moreover, this study aims to shed light on unexplored biological pathways within Mycobacterium tuberculosis by investigating unidentified hypothetical proteins. The findings of this prospective research hold the promise of providing valuable insights into potential treatment targets, leading to a subsequent thorough structural analysis involving the investigation of protein-protein interactions, validation, modeling, quality assessment, and ultimately, molecular docking. Hence, establishing a solid groundwork for future studies and drug discovery initiatives. Ultimately, these targets have the potential to significantly reduce the global burden of TB and enhance patient outcomes, pending successful experimental validation and subsequent translation into clinical applications.

The online version contains supplementary material available at 10.1007/s12088-025-01473-0.