PROXIMAL: a method for Prediction of Xenobiotic Metabolism.
PROXIMAL: a method for Prediction of Xenobiotic Metabolism.
复制标题
DOI：
10.1186/s12918-015-0241-4
复制
发表时间：
2015-12-22
影响因子：
--
通讯作者：
Hassoun S
中科院分区：
文献类型：
--
作者：
Yousofshahi M;Manteiga S;Wu C;Lee K;Hassoun S
生物活性化学品对环境的污染已成为潜在的公共卫生风险。这些可能导致人类痛苦或疾病的物质可以在空气、水和食品供应中找到。一个悬而未决的问题是，这些化学物质是否通过体内表达的异生物质代谢酶转化为潜在更具活性或毒性更强的衍生物。我们提出了一种新的预测工具，称为 PROXIMAL（异生物质代谢预测），用于识别肝脏中异生物质化学物质可能的转化产物。 PROXIMAL 使用 DrugBank 和 KEGG 的反应数据构建查找表，对 I 期和 II 期酶进行结构修饰的位点和类型进行分类。给定感兴趣的化合物，PROXIMAL 搜索与查找表中编录的位点相匹配的子结构，应用相应的修改来生成一组可能的转化产物，并根据所涉及酶的活性和丰度对产物进行排名。 PROXIMAL 通过分析化学物质的子结构，生成特定于目标化学物质的转换。我们通过对两种疑似内分泌干扰活性的环境化学物质双酚 A (BPA) 和 4-氯联苯 (PCB3) 的案例研究来评估 PROXIMAL 预测的准确性。与已发表的报告进行比较，分别证实了 BPA 和 PCB3 的 7 种预测衍生物中的 5 种和 26 种预测衍生物中的 17 种。我们还将 PROXIMAL 生成的生物转化预测与另外两种预测工具 METEOR 和 Metaprint2D-react 生成的生物转化预测进行了比较。 PROXIMAL 可以预测含有人类肝酶可识别子结构的化学物质的转化。它还能够根据参与外源转化的酶的活性和丰度对预测的代谢物进行排序。本文的在线版本 (doi:10.1186/s12918-015-0241-4) 包含补充材料，可供授权用户使用。
Contamination of the environment with bioactive chemicals has emerged as a potential public health risk. These substances that may cause distress or disease in humans can be found in air, water and food supplies. An open question is whether these chemicals transform into potentially more active or toxic derivatives via xenobiotic metabolizing enzymes expressed in the body. We present a new prediction tool, which we call PROXIMAL (Prediction of Xenobiotic Metabolism) for identifying possible transformation products of xenobiotic chemicals in the liver. Using reaction data from DrugBank and KEGG, PROXIMAL builds look-up tables that catalog the sites and types of structural modifications performed by Phase I and Phase II enzymes. Given a compound of interest, PROXIMAL searches for substructures that match the sites cataloged in the look-up tables, applies the corresponding modifications to generate a panel of possible transformation products, and ranks the products based on the activity and abundance of the enzymes involved. PROXIMAL generates transformations that are specific for the chemical of interest by analyzing the chemical’s substructures. We evaluate the accuracy of PROXIMAL’s predictions through case studies on two environmental chemicals with suspected endocrine disrupting activity, bisphenol A (BPA) and 4-chlorobiphenyl (PCB3). Comparisons with published reports confirm 5 out of 7 and 17 out of 26 of the predicted derivatives for BPA and PCB3, respectively. We also compare biotransformation predictions generated by PROXIMAL with those generated by METEOR and Metaprint2D-react, two other prediction tools. PROXIMAL can predict transformations of chemicals that contain substructures recognizable by human liver enzymes. It also has the ability to rank the predicted metabolites based on the activity and abundance of enzymes involved in xenobiotic transformation. The online version of this article (doi:10.1186/s12918-015-0241-4) contains supplementary material, which is available to authorized users.