A Multi-pronged Computational Approach to Advance Kinase Drug Discovery

项目摘要/摘要 近年来，计算速度呈指数级增长；然而，计算AP的潜力-- 加速药物发现的方法还没有完全实现。我们的长期目标是发展和应用- 使用计算工具来推进基于结构的药物设计。这项建议的目标是应用新的 基于前沿分子模拟和量子计算工具的计算协议攻关 合理设计可逆和靶向的激酶共价抑制剂(TCI)中的几个关键问题。蛋白水解酶 磷酸化三分之一的蛋白质组和解除对激酶功能的调控是调控癌症的主要策略， 自身免疫性和fl炎症状态。近年来，可逆的和共价的激酶抑制剂正在获得 FDA的批准以快速增长的速度。 在我们的新工具开发、试点研究、未公布的初步数据以及工作假设的支持下- SES，我们将追求三个特定的fic目标：1)进行广泛的基因组和蛋白质组计算程序研究，以 确定共价靶向位点；2)阐明反应机理和结构-可逆性关系 用于化学弹头设计；3)阐明控制可逆反应选择性和动力学的机制。 这是一种激酶抑制剂。这些研究的结果将指导目前在TCI发现激酶和 寻找新的可用药靶点；提供减少药物反应性和可逆性的详细知识 化学弹头以最大限度地减少毒性；并提供新的战略来提高选择性和动力学参数 可逆的抑制剂。该项目的成功完成将使我们能够建立一个计算平台来 推进基于结构的药物设计，拓展当前治疗靶点空间。

Project Summary/Abstract In recent years, computing speed has exponentially increased; however, the potential of computational ap- proaches to accelerate drug discovery has not been fully realized. Our long-term goal is to develop and ap- ply computational tools to advance structure-based drug design. The objective of this proposal is to apply new computational protocols based on the cutting-edge molecular simulation and quantum calculation tools to tackle several critical topics in the rational design of reversible and targeted covalent inhibitors (TCI) of kinases. Kinases phosphorylate a third of the proteome and deregulation of kinase functions is a major strategy to modulate cancer, autoimmune and inflammatory conditions. In recent years, reversible and covalent kinase inhibitors are gaining FDA approvals at a rapidly growing speed. Supported by our new tool developments, pilot studies, unpublished preliminary data, as well as working hypothe- ses, we will pursue three specific aims: 1) conduct kinome and proteome wide computational profiling studies to identify covalent targetable sites; 2) elucidate the reaction mechanisms and structure-reversibility relationships for chemical warhead design; and 3) elucidate the mechanisms controlling selectivity and kinetics of reversible kinase inhibitors. The outcomes of the studies will guide the current efforts in TCI discovery for kinases and the search for new druggable targets; provide detailed knowledge for attenuating reactivity and reversibility of chemical warheads to minimize toxicity; and offer new strategies to improve selectivity and kinetic parameters of reversible inhibitors. Successful completion of the project will allow us to build a computational platform to advance structure-based drug design and expand the current therapeutic target space.