4.4 Article

3D QSAR study on substituted 1, 2, 4 triazole derivatives as anticancer agents by kNN MFA approach

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SAUDI PHARMACEUTICAL JOURNAL
卷 31, 期 12, 页码 -

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ELSEVIER
DOI: 10.1016/j.jsps.2023.101836

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3D-QSAR; Genetic algorithm; Anticancer agents; 4-Triazole

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Utilizing the k-Nearest Neighbor-Molecular Field Analysis (kNN-MFA) method, a 3D QSAR evaluation was conducted on substituted 1, 2, and 4-triazole derivatives for their anti-cancer potential. The study revealed a strong correlation between biological activity and descriptors, demonstrating the significant pharmacological role of these derivatives in potentially identifying chemical compounds with optimal anticancer activity and minimal side effects.
Background and objectives: Researchers have recently focused on the biological and synthetic effects of 1, 2, and 4-triazole fused heterocyclic molecules because they have tremendous medicinal value. The objective of the pre-sent study was to carry out the 3D QSAR evaluation on the substituted 1,2, and 4 triazole derivatives for anti-cancer potential using k-Nearest Neighbor-Molecular Field Analysis (kNN-MFA) method.Methods: Using the molecular design suite, a three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was undertaken on a series of 4-amino-5-(pyridin3yl)-4H-1, 2, and 4-triazole-3-thiol anticancer drugs (Vlife MDS). This study used a genetic algorithm and a manual selection approach on 20 substituted 1, 2, and 4-triazole derivatives. Based on the genetic algorithm (GA), the 3D-QSAR model was generated. Statistical significance and predictive capacity were evaluated using internal and external validation.Results: The most significant model has a correlation coefficient of 0.9334 (squared correlation coefficient r2 = 0.8713), showing that biological activity and descriptors have a strong relationship. The model exhibited internal predictivity of 74.45 percent (q2 = 0.2129), external predictivity of 81.09 percent (pred r2 = 0.8417), and the smallest error term for the predictive correlation coefficient (pred r2se = 0.1255). The model revealed steric (S 1047--0.0780--0.0451S 927) and electrostatic (E 1002) data points that contribute remarkably to anticancer activity. A molecular field study demonstrates a link between the structural features of substituted triazole de-rivatives and their activities.Conclusion: The good-to-moderate anticancer potential of compounds confirms the significant pharmacological role of 1,2,4-triazole derivatives. These results could lead to the identification of potential chemical compounds with optimal anticancer activity and minimal side effects.

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