Cytochrome P450 Models for Risk Assessment

描述(由申请人提供)：这笔赠款的继续将支持继续开发用于预测细胞色素P450介导的区域选择性和比率的计算工具。细胞色素P450酶家族负责大量化学物质的代谢。该酶家族还负责许多化学物质对活性中间体的生物激活，从而导致毒性和致癌性。因此，该酶家族的计算模型将在科学和公共卫生的许多领域发挥重要作用。这项提议的总体目标是建立可用作风险评估组成部分的计算模型。这些方法将同样适用于工业过程中更安全的化学品的设计，作为药物设计的工具，以及作为化学品虚拟图书馆的毒性评估工具。具体地说，这笔赠款将1)扩展现有的计算模型，以包括更多的P450介导的反应，2)进行允许预测P450介导的反应速率的实验，以及3)建立参与毒素和致癌物生物激活的最重要的P450酶之一--细胞色素P450酶的三维结合亲和力模型。实验设计结合了有机合成、分子生物学、蛋白质生物化学、分析质谱学、放射化学方法学和计算化学。因此，这项建议还有助于培训科学家在化学/生物界面上使用多学科方法来理解特定的科学问题。

DESCRIPTION (provided by applicant): The continuation of this grant will support the continued development of computational tools for predicting cytochrome P450 mediated regioselectivities and rates. The cytochrome P450 enzyme family is responsible for metabolism of a large number of chemicals. This enzyme family is also responsible for the bioactivation of many chemicals to reactive intermediates responsible for toxicity and carcinogenicity. Therefore, computational models for this enzyme family will play an important role in many areas of science and public health. The overall goal of this proposal is to establish computational models that can be used as a component in risk assessment. These methods will be equally applicable to the design of safer chemicals for industrial processes, as tools for drug design, and as tools for the toxicity assessment of virtual libraries of chemicals. Specifically, this grant will 1) extend existing computational models to include more P450 mediated reactions, 2) perform experiments that will allow for the prediction of the rates of P450 mediated reactions, and 3) establish 3-dimensional binding affinity models for CYP2E1, one of the most important P450 enzymes involved in the bioactivation of toxins and carcinogens. The experimental design combines the use of organic synthesis, molecular biology, protein biochemistry, analytical mass spectrometry, radiochemical methodology, and computational chemistry. Thus, this proposal also helps to train scientists in the use of multidisciplinary approaches, at the chemical/biological interface, to understanding a given scientific problem.