Department of Organic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, Santiago de Compostela, Spain.
Pest Manag Sci. 2011 Apr;67(4):438-45. doi: 10.1002/ps.2082. Epub 2011 Jan 6.
The increasing resistance of several phytopathogenic fungal species to existing agrochemical fungicides has alarmed the worldwide scientific community. In an attempt to overcome this problem, a discriminant model based on substructural descriptors was developed from a heterogeneous database of compounds for the design of, search for and prediction of agrochemical fungicides.
The discriminant model classifies correctly 81.95% of the fungicides and 81.54% of the inactive compounds in the training series, with an accuracy of 81.72%. In the prediction series, the percentage of correct classification was 80.59 and 85.56% for fungicides and inactive compounds respectively, with an accuracy of 83.44%. Some fragments were extracted and their contributions were calculated. From the fragments that were determined to make positive contributions to the fungicidal activity, new molecules such as pyrrole derivatives were designed and the probabilities of their being fungicides were calculated. These molecules were correctly classified as potential fungicides.
The discriminant model based on substructural descriptors provides a promising methodology for the development of molecular patterns to be used in the design of, search for and prediction of agrochemical fungicides of wide spectrum. This constitutes an alternative for the discovery of compounds that are able to decrease crop losses caused by phytopathogenic fungal species.
几种植物病原真菌对现有农用杀菌剂的抗性不断增加，引起了全球科学界的警觉。为了解决这个问题，我们从一个化合物的异构数据库中开发了一个基于亚结构描述符的判别模型，用于农用杀菌剂的设计、搜索和预测。
判别模型正确地对训练系列中的 81.95%的杀菌剂和 81.54%的非活性化合物进行了分类，准确率为 81.72%。在预测系列中，杀菌剂和非活性化合物的正确分类百分比分别为 80.59%和 85.56%，准确率为 83.44%。提取了一些片段并计算了它们的贡献。从对杀菌活性有积极贡献的片段中，设计了一些新的分子，如吡咯衍生物，并计算了它们作为杀菌剂的概率。这些分子被正确地归类为潜在的杀菌剂。
基于亚结构描述符的判别模型为开发用于设计、搜索和预测广谱农用杀菌剂的分子模式提供了一种很有前途的方法。这为发现能够减少植物病原真菌引起的作物损失的化合物提供了一种替代方法。
