ABSTRACT

Chagas disease is endemic to 21 Latin American countries and is a great public health problem in that region. Current chemotherapy remains unsatisfactory; consequently the need to search for new drugs persists. Here we present a new approach to identify novel compounds with potential anti-chagasic action. A large dataset of 584 compounds, obtained from the Drugs for Neglected Diseases initiative, was selected to develop the computational model. Dragon software was used to calculate the molecular descriptors and WEKA software to obtain the classification tree. The best model shows accuracy greater than 93.4% for the training set; the tree was also validated using a 10-fold cross-validation procedure and through a test set, achieving accuracy values over 90.5% and 92.2%, correspondingly. The values of sensitivity and specificity were around 90% in all series; also the false alarm rate values were under 10.5% for all sets. In addition, a simulated ligand-based virtual screening for several compounds recently reported as promising anti-chagasic agents was carried out, yielding good agreement between predictions and experimental results. Finally, the present work constitutes an example of how this rational computer-based method can help reduce the cost and increase the rate in which novel compounds are developed against Chagas disease.

摘要

恰加斯病是21个拉丁美洲国家的特有疾病，是该地区的一个巨大的公共卫生问题。目前的化学疗法仍然不能令人满意；因此，仍然需要寻找新药。在这里，我们提出了一种新的方法来鉴定具有潜在抗chagasic作用的新型化合物。选择了从被忽视疾病药物计划中获得的584种化合物的大型数据集，以开发计算模型。使用Dragon软件计算分子描述符，并使用WEKA软件获得分类树。最佳模型显示训练集的准确性大于93.4％；还使用10倍交叉验证程序并通过测试集对树进行了验证，分别达到了90.5％和92.2％以上的精度值。在所有系列中，敏感性和特异性的值约为90％。所有组的误报率值均低于10.5％。另外，对最近报道为有前景的抗甲壳类药物的几种化合物进行了基于配体的模拟虚拟筛选，从而在预测和实验结果之间取得了良好的一致性。最后，本工作构成了这种基于计算机的合理方法如何帮助降低成本并提高新型药物开发能力以抵抗南美锥虫病的例子。