Instituto de Química de São Carlos, Universidade de São Paulo, São Carlos, SP 13566-590, Brazil.
Molecules. 2013 Apr 29;18(5):5032-50. doi: 10.3390/molecules18055032.
Quantitative structure-activity relationship (QSAR) studies were performed in order to identify molecular features responsible for the antileishmanial activity of 61 adenosine analogues acting as inhibitors of the enzyme glyceraldehyde 3-phosphate dehydrogenase of Leishmania mexicana (LmGAPDH). Density functional theory (DFT) was employed to calculate quantum-chemical descriptors, while several structural descriptors were generated with Dragon 5.4. Variable selection was undertaken with the ordered predictor selection (OPS) algorithm, which provided a set with the most relevant descriptors to perform PLS, PCR and MLR regressions. Reliable and predictive models were obtained, as attested by their high correlation coefficients, as well as the agreement between predicted and experimental values for an external test set. Additional validation procedures were carried out, demonstrating that robust models were developed, providing helpful tools for the optimization of the antileishmanial activity of adenosine compounds.
为了确定 61 种腺苷类似物作为利什曼原虫(LmGAPDH)甘油醛 3-磷酸脱氢酶抑制剂的抗利什曼活性的分子特征,进行了定量构效关系(QSAR)研究。采用密度泛函理论(DFT)计算量子化学描述符,同时使用 Dragon 5.4 生成了几个结构描述符。采用有序预测器选择(OPS)算法进行变量选择,该算法提供了一组与执行 PLS、PCR 和 MLR 回归最相关的描述符。可靠和可预测的模型得到了验证,这证明了它们具有较高的相关系数,以及外部测试集的预测值与实验值之间的一致性。还进行了其他验证程序,证明了稳健模型的开发,为优化腺苷化合物的抗利什曼活性提供了有用的工具。