Predicting Rates and Regioselectivity in Cytochrome P450 Mediated Reactions

预测细胞色素 P450 介导反应的速率和区域选择性

• 批准号: 7876607
• 负责人: Jeffrey P Jones
• 金额: $ 31.82万
• 依托单位: WASHINGTON STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-02-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7876607
• 关键词: Address; Affinity; Apoproteins; Applications Grants; Benchmarking; Benign; Binding; Cancer Etiology; Code; Computer Simulation; Computer software; Computing Methodologies; Cytochrome P450; Data Set; Databases; Descriptor; Drug Design; Drug Interactions; Electronics; Enzymes; Excretory function; Family; Goals; Grant; Heme; Heme Iron; Homeostasis; Housing; Iron; Isotopes; Knowledge; Life; Measures; Mediating; Metabolic; Metabolism; Methods; Modeling; Nitrogen; Oxygen; Pathway interactions; Pharmaceutical Preparations; Public Domains; Publications; Publishing; Reaction; Reactive Oxygen Species; Relative (related person); Research; Research Personnel; Risk Assessment; Series; Site; Source Code; Specificity; System; Testing; Threonine; Time; Toxic effect; Translating; Validation; Work; absorption; abstracting; base; computerized tools; design; drug development; drug metabolism; inhibitor/antagonist; meetings; mutant; novel therapeutics; open source; oxene; oxidation; predictive modeling; prevent; protonation; public health relevance; software development; therapeutic target; tool; two-dimensional; virtual; web site

DESCRIPTION (provided by Applicant): Summary and Abstract- The main goals of this proposal are 1) to provide the fundamental knowledge required for understanding Cytochrome P450 mediated reaction mechanism with regards to rates, regioselectivity, and binding, and 2) to provide computational tools for predicting the metabolic component of ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity). These are highly significant goals that will positively impact almost all drug development projects and decrease the time required to develop new therapeutics. These goals will be described in terms of the following four Specific Aims: Aim 1) At present the number of active-oxygen species used by Cytochrome P450 remains controversial, and we propose that this may explain why predictive methods for metabolism are limited to around 85% accuracy. Predictive models for metabolism are important in drug design, and have the potential to save lives by decreasing the time it takes to develop new drugs. Aim 2) Specific Aim 2 explores binding afforded to substrates designed to coordinate to the iron of the heme (type II binding) providing specificity for P450 enzymes by increasing affinity up to 250-fold. This is significant because systemic administration of drugs meant to inhibit a single P450 enzyme normally leads to broad inhibition of a number of P450 enzymes, upsetting homeostasis, and causing drug-drug interactions. Aim 3) Computational prediction of P450 mediated rates remains one of the most important targets of researchers working in the field. Specific Aim 3 will establish the features important in such predictions. If this goal can be met we can understand the important features involved in predicting the clearance of a drug from the body, and we move closer to the goal of virtual drug design. Aim 4) With the ever-expanding number of computational methods and research publications in predictive ADMET, Specific Aim 4 will provide common sets of publicly accessible test set databases along with open-source predictive code allowing different computational ADMET methods to be tested against common benchmarks. This is particularly important since the majority of the methods are developed in-house and the test sets are not published. We hypothesize that by publishing open source code to a public web site for metabolic predictions that we can translate the results of ours' and others' research into the public domain resulting in a significant increase in the use and quality of these tools. We also hypothesize that having a common set of data available to all researchers will encourage validation, comparison, and enhancement of ADMET models. Public Health Relevance: Narrative- The purpose of this grant application is to understand the important features of cytochrome P450 enzymes with respect to drug metabolism, and drug design. Cytochrome P450 enzymes are the most important drug metabolizing enzymes and are responsible for most drug metabolism. While the majority of the reactions mediated by this enzymes family are benign, a number cause activation to reactive species that can cause cancer and toxicity. Furthermore, many life threatening drug-drug interactions occur from drugs slowing cytochrome P450 mediated reactions. This grant application will develop methods to design new drugs faster, and safer than we can presently through an increased understanding of the rates and binding affinities or P450 mediated reactions.

描述（由申请人提供）：总结和摘要-本提案的主要目标是1）提供理解细胞色素P450介导的反应机制所需的关于速率、区域选择性和结合的基础知识，以及2）提供预测ADMET代谢组分（吸收、分布、代谢、排泄、毒性）的计算工具。这些都是非常重要的目标，将积极影响几乎所有的药物开发项目，并减少开发新疗法所需的时间。这些目标将根据以下四个具体目标进行描述：目标1）目前，细胞色素P450使用的活性氧种类的数量仍然存在争议，我们认为这可以解释为什么代谢预测方法的准确性仅限于85%左右。代谢预测模型在药物设计中非常重要，并且有可能通过减少开发新药所需的时间来挽救生命。目的2）特异性目的2探索了与设计为与血红素的铁配位的底物的结合（II型结合），通过增加高达250倍的亲和力来提供对P450酶的特异性。这是重要的，因为全身施用旨在抑制单一P450酶的药物通常导致许多P450酶的广泛抑制，扰乱体内平衡，并引起药物-药物相互作用。目的3）P450介导率的计算预测仍然是该领域研究人员最重要的目标之一。具体目标3将确定在这种预测中重要的特征。如果这一目标能够实现，我们就可以理解预测药物从体内清除的重要特征，我们就离虚拟药物设计的目标更近了。目标4）随着预测ADMET中计算方法和研究出版物数量的不断增加，Specific Aim 4将提供公共可访问的测试集数据库的通用集，沿着开源预测代码，允许针对通用基准测试不同的计算ADMET方法。这一点特别重要，因为大多数方法都是内部开发的，测试集没有公布。我们假设，通过将开源代码发布到公共网站进行代谢预测，我们可以将我们和其他人的研究结果转化为公共领域，从而显着增加这些工具的使用和质量。我们还假设，有一个共同的数据集提供给所有的研究人员将鼓励验证，比较和增强ADMET模型。 公共卫生相关性：叙述-本资助申请的目的是了解细胞色素P450酶在药物代谢和药物设计方面的重要特征。细胞色素P450酶是最重要的药物代谢酶，负责大多数药物代谢。虽然由这种酶家族介导的大多数反应是良性的，但一些反应会导致活性物质的活化，从而导致癌症和毒性。此外，许多危及生命的药物相互作用发生在减缓细胞色素P450介导的反应的药物上。这项拨款申请将开发方法，通过增加对P450介导反应的速率和结合亲和力的理解，比我们目前更快，更安全地设计新药。