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3D QSAR and pharmacophore modeling studies on C-2 and C-4 substituted Quinazoline series as Anti-tubercular agents

机译:C-2和C-4取代喹唑啉系列作为抗结核药的3D QSAR和药效团建模研究

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Antitubercular drug discovery is a challenging strain in the recent era. Quinazolines are an important chemical compounds having diverse significant biological activities. Three dimensional Quantitative structure-activity relationships ( 3D QSAR) represent an attempt to correlate three dimensional structural features of compounds with biological activities. The pharmacophore identification and QSAR studies on C-2 and C-4 substituted quinazoline series was carried out by partial least-squares (PLS) method to identify the potential framework of the molecules responsible for the antitubercular activity. The QSAR models were developed considering training and test set approaches further validated for statistical significance and predictive ability by internal and external validation. The results of 3D QSAR model demonstrate the high degree of statistical importance and excellent predictive capability. The hydrogen bond accepter, hydrogen bond donor, positively charged, aromatic carbon, steric and hydrophobic parameter are the important features contributing towards the activity. The selected best QSAR model A has a training set of 20 molecules and test set of 6 molecules with correction coefficient of 0.9641.
机译:在最近的时代,抗结核药物的发现是具有挑战性的。喹唑啉是具有多种重要生物活性的重要化合物。三维定量结构-活性关系(3D QSAR)表示尝试将化合物的三维结构特征与生物活性相关联。通过部分最小二乘(PLS)方法对C-2和C-4取代的喹唑啉系列进行了药效基团鉴定和QSAR研究,以鉴定负责抗结核活性的分子的潜在结构。开发QSAR模型时考虑了训练和测试集方法,并通过内部和外部验证进一步验证了统计意义和预测能力。 3D QSAR模型的结果证明了高度的统计重要性和出色的预测能力。氢键受体,氢键供体,带正电荷,芳族碳,空间和疏水参数是有助于该活性的重要特征。所选的最佳QSAR模型A的训练集为20个分子,测试集为6个分子,校正系数为0.9641。

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