Ferreira Leonardo G, Andricopulo Adriano D
Laboratório de Quimica Medicinal e Computacional, Instituto de Física de São Carlos, Universidade de São Paulo, Av. Trabalhador São-Carlense 400, 13560-970, São Carlos- SP, Brazil.
Curr Comput Aided Drug Des. 2012 Dec 1;8(4):309-16. doi: 10.2174/157340912803519589.
Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r²=0.98 and q²=0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pKi values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.
醛缩酶已成为治疗人类非洲锥虫病的一个有前景的分子靶点。在过去几年中，由于感染布氏锥虫的患者数量不断增加，迫切需要新的药物来治疗这种被忽视的疾病。在本研究中，针对一系列醛缩酶抑制剂生成了基于片段的二维定量构效关系（QSAR）模型。通过应用留一法和留多法交叉验证程序，获得了显著的相关系数（r² = 0.98和q² = 0.77），表明模型具有统计学上的内部和外部一致性。最佳模型用于预测一系列测试集化合物的pKi值，预测值与实验结果吻合良好，显示出该模型对未测试化合物的预测能力。此外，还进行了基于结构的分子建模研究，以研究抑制剂在寄生虫靶酶活性位点的结合模式。结构和QSAR结果为设计该结构类别的新型醛缩酶抑制剂提供了有用的分子信息。
