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

结合计算和经典药物化学方法,发现新型吡咯类化合物作为潜在的抗结核药物。

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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.

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