Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.
J Chem Inf Model. 2012 Mar 26;52(3):655-69. doi: 10.1021/ci200622d. Epub 2012 Feb 29.
Biodegradation is the principal environmental dissipation process. Due to a lack of comprehensive experimental data, high study cost and time-consuming, in silico approaches for assessing the biodegradable profiles of chemicals are encouraged and is an active current research topic. Here we developed in silico methods to estimate chemical biodegradability in the environment. At first 1440 diverse compounds tested under the Japanese Ministry of International Trade and Industry (MITI) protocol were used. Four different methods, namely support vector machine, k-nearest neighbor, naïve Bayes, and C4.5 decision tree, were used to build the combinatorial classification probability models of ready versus not ready biodegradability using physicochemical descriptors and fingerprints separately. The overall predictive accuracies of the best models were more than 80% for the external test set of 164 diverse compounds. Some privileged substructures were further identified for ready or not ready biodegradable chemicals by combining information gain and substructure fragment analysis. Moreover, 27 new predicted chemicals were selected for experimental assay through the Japanese MITI test protocols, which validated that all 27 compounds were predicted correctly. The predictive accuracies of our models outperform the commonly used software of the EPI Suite. Our study provided critical tools for early assessment of biodegradability of new organic chemicals in environmental hazard assessment.
生物降解是主要的环境消散过程。由于缺乏全面的实验数据、高研究成本和耗时，因此鼓励使用计算方法来评估化学品的可生物降解性，这是当前一个活跃的研究课题。在这里，我们开发了用于估算环境中化学物质生物降解性的计算方法。首先，使用了日本国际贸易和工业部（MITI）协议下测试的 1440 种不同化合物。分别使用支持向量机、k-最近邻、朴素贝叶斯和 C4.5 决策树这四种不同方法，使用物理化学描述符和指纹分别构建了易于生物降解与不易生物降解的组合分类概率模型。对于 164 种不同化合物的外部测试集，最佳模型的整体预测准确率均超过 80%。通过结合信息增益和子结构片段分析，进一步确定了一些优先的易于生物降解或不易生物降解的化学物质的子结构。此外，通过日本 MITI 测试方案选择了 27 种新的预测化学品进行实验测定，验证了这 27 种化合物均被正确预测。我们的模型预测准确率优于常用的 EPI Suite 软件。我们的研究为环境危害评估中新型有机化学品生物降解性的早期评估提供了关键工具。
