Novel Computational Methods for Modeling Cytochrome P450 Mediated Drug Metabolism

描述（由申请方提供）：通过细胞色素P450酶（CYP）代谢药物和其他外源性物质是人体的基本解毒和药物清除机制。尽管自2000年以来发表了几种X射线结构，但药物代谢的可靠计算预测仍然是一个巨大的挑战。在这项资助申请中，我们提出了一种整合的高通量方法，该方法将配体的电子特性与蛋白质的结构特性相结合。我们的主要目标是开发和应用创新的基于结构的设计技术，解决当前方法的严重缺陷。特别是，我们已经扩展了我们的新的对接概念，将所有观察到的形式的蛋白质的灵活性相关的配体-双链相互作用，熵的贡献影响预测的结合姿势，我们将添加对飞行溶剂化配体-双链复合物。为了提高对接质量，我们将优化为研究的每种酶量身定制的评分函数的参数。结合最初的重点有效计算的氢提取能量，我们将预测区域选择性代谢的药物或候选药物结合CYP。基于所得的对接姿势，将进行多维QSAR模拟，以准确定量结合亲和力作为CYP抑制的量度，并对结合模式进行更好的排序。新的计算方法将被应用到两个重要的药物代谢酶（CYP 2C 9，3A 4）。生成的计算模型将存储在数据库中并公开提供。其他研究人员将被邀请通过一个安全的网络协议来筛选化合物，以预测药物代谢和抑制作用。其他研究人员提交的数据将对模型的性能和适用性提供宝贵的反馈。 公共卫生相关性：细胞色素P450介导的药物代谢对所给药物的疗效起着关键作用。该项目旨在开发和应用创新的计算方法，以有效地预测药物代谢以及药物代谢酶的抑制。由此产生的计算模型允许在药物发现早期估计药物效率和潜在的不良反应，从而对药物开发产生强烈影响。

DESCRIPTION (provided by applicant): The metabolism of drugs and other xenobiotics by cytochrome P450 enzymes (CYP) is an essential detoxification and drug clearance mechanism in humans. Despite the publication of several X-ray structures since 2000, reliable computational prediction of drug metabolism remains a huge challenge. In this grant application, we propose an integrative high-throughput approach that combines electronic properties of a ligand with structural properties of the protein. Our main aim is the development and application of innovative structure-based design techniques that address serious shortcomings of current approaches. In particular, we have extended our novel docking concept to incorporate all observed forms of protein flexibility relevant for ligand-CYP interactions, entropic contributions influencing the prediction of binding poses, and we will add on- the-fly solvation to ligand-CYP complexes. To improve the docking quality we will optimize the parameters of a scoring function tailor-made for each CYP enzyme studied. In combination with an initial focus on efficient calculation of hydrogen-abstraction energies we will predict regioselective metabolism of drugs or drug candidates binding to CYPs. Based on the resulting docking poses, multidimensional QSAR simulations will be performed for accurate quantification of binding affinity as a measure CYP-inhibition and better ranking of binding modes. The new computational methods will be applied to two CYP enzymes (CYP2C9, 3A4) important in drug metabolism. The generated computational models will be stored in a database and made publicly available. Other researchers will be invited to screen compounds against our CYP database via a secure Web protocol to predict drug metabolism and inhibition. The submission of data by other researchers will provide valuable feedback on the performance and applicability of the models. PUBLIC HEALTH RELEVANCE: Cytochrome P450 mediated drug metabolism plays a critical role for the efficacy of administered drugs. This project is aimed toward developing and applying innovative computational methods to efficiently predict drug metabolism as well as inhibition of the drug metabolizing enzymes. The resulting computational models allow for the estimation of drug efficiency and the potential of adverse reactions early in drug discovery and thus have a strong impact on drug development.