Combined computational and classical medicinal chemistry procedure to disclose novel pyrrole-based compounds as potential antituberculosis agents

Abstract Tuberculosis (TB) remains a major global health challenge, worsened by the rise of multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains. In this study, we employed a combined computational and medicinal chemistry approach to design, synthesize, and evaluate new pyrrole-based analogues of Sudoterb ( 1 , LL-3858) as potential anti-TB agents. Ligand-based quantitative structure–activity relationships (QSAR) and 3-D QSAR models, as well as structure-based docking and COMBINE analyses, were developed and used to analyze the anti-TB structural determinants and investigate the putative targeting to the MmpL3 transporter. Nineteen new analogues, belonging to amide ( 2a–j ) and carbamate ( 3a–i ) series, were synthesized and tested against Mycobacterium tuberculosis H37Rv resistant strain using the microplate Alamar Blue assay. Most of the synthesized analogues showed enhanced potency compared to Sudoterb (MIC = 20.7 µM), with 2i (MIC = 2.8 µM) and 3 h (MIC = 2.4 µM) emerging as the most potent and selective derivatives (IC 50 > 80 µM in Vero cells). Computational predictions aligned well with experimental results, validating the modeling workflow. These findings identify 2i and 3 h as promising lead compounds and highlight the utility of integrating computational modeling with rational synthesis to accelerate anti-TB drug discovery.