Tuberculosis (TB) is an infectious disease that primarily affects the lungs in humans and accounts for theMycobacterium tuberculosis(Mtb) bacteria as the etiologic agent. According to the World Health Organization (WHO), over 10 million people are affected by TB in various forms and it is ranked among the top 10 causes of mortality, making it a significant global health threat. In this study, we introduce a computational framework designed to identify the important chemical features crucial for effectively inhibiting Mtb CAs. Through the application of a mechanistic interpretation model, we elucidated the essential features pivotal for robust inhibition. Utilizing this model, we have engineered molecules that not only exhibit potent inhibitory activity but also introduce relevant novel chemistry. The designed molecules were prioritized for their synthesis based on their predicted pKI values via the QSAR model. All the rationally designed and synthesized compounds were evaluatedin vitroagainst different carbonic anhydrase isoforms expressed from the pathogenMycobacterium tuberculosis, moreover, the off-target and widely human-expressed CA I and II were also evaluated. Among the reported derivatives,2,4,and5demonstrated the most valuablein vitroactivity resulting in promising candidates for the treatment of TB. Further, the molecules having good prediction accuracies with the prior established mechanistic and ML-QSAR models were utilized to delve deeper into the realm of the systems biology to understand their mechanism in combating tuberculotic pathogenesis. The results pointed to the key involvement of the compounds in modulating immune responses via NF-κβ1, SRC kinase, and TNF-α to modulate the granuloma formation and its clearance via T cells. This dual action, inhibiting the pathogen’s enzyme while modulating the human immune machinery, represents a paradigm shift towards more effective and comprehensive treatment approaches in combating tuberculosis.Graphical Abstract
