Adeniji Shola Elijah, Uba Sani, Uzairu Adamu
Department of Chemistry, Ahmadu Bello University, Zaria, Nigeria.
J Pathog. 2018 May 10;2018:1018694. doi: 10.1155/2018/1018694. eCollection 2018.
A quantitative structure-activity relationship (QSAR) study was performed to develop a model that relates the structures of 50 compounds to their activities against . The compounds were optimized by employing density functional theory (DFT) with B3LYP/6-31G. The Genetic Function Algorithm (GFA) was used to select the descriptors and to generate the correlation model that relates the structural features of the compounds to their biological activities. The optimum model has squared correlation coefficient () of 0.9202, adjusted squared correlation coefficient () of 0.91012, and leave-one-out (LOO) cross-validation coefficient () value of 0.8954. The external validation test used for confirming the predictive power of the built model has pred value of 0.8842. These parameters confirm the stability and robustness of the model. Docking analysis showed the best compound with high docking affinity of -14.6 kcal/mol which formed hydrophobic interaction and hydrogen bond with amino acid residues of cytochromes (Mtb CYP121). QSAR and molecular docking studies provide valuable approach for pharmaceutical and medicinal chemists to design and synthesize new anti- compounds.
进行了定量构效关系（QSAR）研究，以建立一个将50种化合物的结构与其对……的活性相关联的模型。通过采用B3LYP/6 - 31G密度泛函理论（DFT）对化合物进行优化。遗传函数算法（GFA）用于选择描述符并生成将化合物的结构特征与其生物活性相关联的相关模型。最佳模型的平方相关系数（）为0.9202，调整后的平方相关系数（）为0.91012，留一法（LOO）交叉验证系数（）值为0.8954。用于确认所构建模型预测能力的外部验证测试的pred值为0.8842。这些参数证实了模型的稳定性和稳健性。对接分析表明，最佳化合物具有-14.6 kcal/mol的高对接亲和力，它与细胞色素（Mtb CYP121）的氨基酸残基形成疏水相互作用和氢键。QSAR和分子对接研究为药物化学家和药物化学家设计和合成新的抗……化合物提供了有价值的方法。
