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DOI 10.1007/s10822-026-00794-6

Медицинская библиотека · Journal of computer-aided molecular design · 2026

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

Ragno Rino, Zwergel Clemens, Valente Sergio, Astolfi Roberta, Lambona Chiara, Proia Eleonora, Giuliani Lidia, Franzblau Scott G, Fioravanti Rossella, Mai Antonello

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

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 (IC50 > 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.

Для цитирования: Ragno Rino, Zwergel Clemens, Valente Sergio, Astolfi Roberta, Lambona Chiara, Proia Eleonora, Giuliani Lidia, Franzblau Scott G, Fioravanti Rossella, Mai Antonello. Combined computational and classical medicinal chemistry procedure to disclose novel pyrrole-based compounds as potential antituberculosis agents.. Journal of computer-aided molecular design. 2026. DOI: 10.1007/s10822-026-00794-6.

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