a Institute of Biomedical Chemistry (IBMC) , Moscow , Russia.
b Medico-biological Faculty , Pirogov Russian National Research Medical University , Moscow , Russia.
SAR QSAR Environ Res. 2017 Oct;28(10):833-842. doi: 10.1080/1062936X.2017.1399165. Epub 2017 Nov 20.
Biotransformation is a process of the chemical modifications which may lead to the reactive metabolites, in particular the epoxides. Epoxide reactive metabolites may cause the toxic effects. The prediction of such metabolites is important for drug development and ecotoxicology studies. Epoxides are formed by some oxidation reactions, usually catalysed by cytochromes P450, and represent a large class of three-membered cyclic ethers. Identification of molecules, which may be epoxidized, and indication of the specific location of epoxide functional group (which is called SOE - site of epoxidation) are important for prediction of epoxide metabolites. Datasets from 355 molecules and 615 reactions were created for training and validation. The prediction of SOE is based on a combination of LMNA (Labelled Multilevel Neighbourhood of Atom) descriptors and Bayesian-like algorithm implemented in PASS software and MetaTox web-service. The average invariant accuracy of prediction (AUC) calculated in leave-one-out and 20-fold cross-validation procedures is 0.9. Prediction of epoxide formation based on the created SAR model is included as the component of MetaTox web-service ( http://www.way2drug.com/mg ).
生物转化是一种化学修饰过程,可能导致反应性代谢物,特别是环氧化物。环氧化物反应性代谢物可能导致毒性作用。此类代谢物的预测对于药物开发和生态毒理学研究非常重要。环氧化物通过某些氧化反应形成,通常由细胞色素 P450 催化,代表一大类三员环醚。识别可能环氧化的分子,并指出环氧化物官能团的特定位置(称为 SOE-环氧化部位)对于预测环氧化物代谢物非常重要。为了训练和验证,创建了 355 个分子和 615 个反应的数据集。SOE 的预测基于标记多级原子邻域 (LMNA) 描述符和贝叶斯样算法的组合,该算法在 PASS 软件和 MetaTox 网络服务中实现。在留一法和 20 折交叉验证过程中计算的平均不变准确性预测 (AUC) 为 0.9。基于创建的 SAR 模型的环氧化物形成预测被包含在 MetaTox 网络服务(http://www.way2drug.com/mg)中。