<p><i>N</i>-heterocyclic derivatives frameworks are a promising axis for antimicrobial discovery, yet aligning cellular efficacy with developability remains challenging. We examined 14 derivatives to derive qualitative structure-activity trends while integrating in-silico filters. Compounds were prepared and assayed by a standardized disc-diffusion test (800&#xa0;µg/disc) against <i>Candida albicans</i>, <i>C. glabrata</i>, <i>Escherichia coli</i>, <i>Pseudomonas aeruginosa</i>, and <i>Staphylococcus aureus</i>, enabling comparison within a matched series. Measurable inhibition zones were observed; for example, compound <b>5</b> ((<i>1&#xa0;H</i>-1,2,4-triazol-1-yl)methanol) gave ≈ 15.2 ± 0.5&#xa0;mm (<i>C. albicans</i>) and ≈ 19.8 ± 0.6&#xa0;mm (<i>C. glabrata</i>), while compound <b>6</b> ((<i>1&#xa0;H</i>-imidazol-1-yl)methanol) showed ≈ 12.8 ± 0.4&#xa0;mm and ≈ 15.3 ± 0.5&#xa0;mm, respectively. Bacterial effects reached &gt; 26&#xa0;mm on <i>E. coli</i> (compound <b>5</b>) and up to 32&#xa0;mm on <i>S. aureus</i> (compound <b>6</b>), compared with ampicillin discs (≈ 14–15&#xa0;mm). In parallel, molecular docking (AutoDock Vina) at mechanistically relevant targets AmpC (1KE4) and CYP51 (5TL8) yielded plausible binding poses with representative affinities in the ≈ − 6 to − 7.8&#xa0;kcal mol<sup>−1</sup> range for several analogues, interpreted qualitatively as mechanistic context rather than rank-order predictors. Overall, this integrated approach provides mechanistic insight and hypothesis-generating SAR, guiding risk-aware prioritization for subsequent quantitative susceptibility testing and focused optimization.</p>

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In silico and in vitro evaluation of N-heterocyclic derivatives as antimicrobials: ADMET analysis, SAR, and molecular docking

  • Zakariae Abbaoui,
  • Oussama Khibech,
  • Ahlam Oulous,
  • Hüseyin Karci,
  • Muhammed Dündar,
  • İlknur Özdemir,
  • Nevin Gürbüz,
  • Ahmet Koç,
  • İsmail Özdemir,
  • Rachid Touzani

摘要

N-heterocyclic derivatives frameworks are a promising axis for antimicrobial discovery, yet aligning cellular efficacy with developability remains challenging. We examined 14 derivatives to derive qualitative structure-activity trends while integrating in-silico filters. Compounds were prepared and assayed by a standardized disc-diffusion test (800 µg/disc) against Candida albicans, C. glabrata, Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus, enabling comparison within a matched series. Measurable inhibition zones were observed; for example, compound 5 ((1 H-1,2,4-triazol-1-yl)methanol) gave ≈ 15.2 ± 0.5 mm (C. albicans) and ≈ 19.8 ± 0.6 mm (C. glabrata), while compound 6 ((1 H-imidazol-1-yl)methanol) showed ≈ 12.8 ± 0.4 mm and ≈ 15.3 ± 0.5 mm, respectively. Bacterial effects reached > 26 mm on E. coli (compound 5) and up to 32 mm on S. aureus (compound 6), compared with ampicillin discs (≈ 14–15 mm). In parallel, molecular docking (AutoDock Vina) at mechanistically relevant targets AmpC (1KE4) and CYP51 (5TL8) yielded plausible binding poses with representative affinities in the ≈ − 6 to − 7.8 kcal mol−1 range for several analogues, interpreted qualitatively as mechanistic context rather than rank-order predictors. Overall, this integrated approach provides mechanistic insight and hypothesis-generating SAR, guiding risk-aware prioritization for subsequent quantitative susceptibility testing and focused optimization.