In-silico Studies of Heterocyclic Benzoxazole Derivatives as an Anticancer Agent: Molecular Docking, 2D and 3D QSAR

Smita J Pawar, Dhanashri Zope, Amol P Kale
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Abstract

In-silico molecular docking studies and QSAR study of benzoxazole derivatives synthesized by Kakkar et al. was done. Comparative studies of docking of 5-flurouracil and 20 compounds revealed considerable interactions, indicating the affinity of newly synthesized compounds for thymidylate synthase. The statistically significant 2D-QSAR models were developed using a molecular design suite (VLifeMDS 4.6). The study was performed with 20 compounds (data set) using sphere exclusion (SE) algorithm, random selection and manual selection methods used for the division of the data set into training and test set. Multiple linear regression [MLR] methodology with stepwise (SW) forward-backward variable selection method was used for building the QSAR models. The results of the 2D-QSAR models were further compared with 3D-QSAR models generated by k-Nearest Neighbor Molecular Field Analysis (kNN-MFA), investigating the substitutional requirements for the favorable anticancer activity against HCT 116 cell line and providing useful information in the characterization and differentiation of their binding sites. The results may be useful for further designing benzoxazole derivatives as anticancer agents prior to synthesis.
作为抗癌剂的杂环苯并噁唑衍生物的室内研究:分子对接、二维和三维 QSAR
研究人员对 Kakkar 等人合成的苯并恶唑衍生物进行了室内分子对接研究和 QSAR 研究。5-flurouracil 和 20 种化合物的对接比较研究显示了相当大的相互作用,表明新合成的化合物对胸腺嘧啶酸合成酶具有亲和力。使用分子设计套件(VLifeMDS 4.6)建立了具有统计意义的二维-QSAR 模型。研究使用球排除(SE)算法、随机选择和手动选择方法将数据集分为训练集和测试集,并对 20 个化合物(数据集)进行了分析。在建立 QSAR 模型时,采用了多元线性回归 [MLR] 方法和逐步(SW)前后向变量选择法。将二维 QSAR 模型的结果与 kNN-MFA 分子场分析法(k-Nearest Neighbor Molecular Field Analysis)生成的三维 QSAR 模型进行了进一步比较,研究了对 HCT 116 细胞系具有良好抗癌活性的替代物要求,并提供了表征和区分其结合位点的有用信息。这些结果可能有助于在合成前进一步设计苯并恶唑衍生物作为抗癌剂。
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