A Multi-pronged Computational Approach to Advance Kinase Drug Discovery

促进激酶药物发现的多管齐下的计算方法

• 批准号: 10097404
• 负责人: Jana Shen
• 金额: $ 36.34万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10097404
• 关键词: Affinity; Amber; Area; Attenuated; Autoimmune; Binding; Chemicals; Collaborations; Coupling; Data; Databases; Development; Disease; Drug Design; Free Energy; Goals; Imatinib; Inflammatory; Kinetics; Knowledge; Letters; Link; MAPK11 gene; Malignant Neoplasms; Methods; Modeling; Molecular; Molecular Conformation; Oncogenic; Opioid Receptor; Outcome Study; Pathway interactions; Pharmaceutical Preparations; Phosphotransferases; Pilot Projects; Process; Proteins; Proteome; Protocols documentation; Protons; Reaction; Scanning; Site; Solvents; Speed; Structure; Testing; Time; Titrations; Toxic effect; Validation; Work; base; cancer therapy; computational platform; computerized tools; design; drug discovery; druggable target; improved; inhibitor/antagonist; insight; kinase inhibitor; molecular dynamics; new therapeutic target; novel; p38 Mitogen Activated Protein Kinase; prospective; protein protein interaction; quantum; rapid growth; residence; simulation; small molecule; therapeutic target; tool; tool development; ubiquitin-protein ligase

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 Supported by our new tool developments, pilot studies, unpublished preliminary data, as well as working hypothe- ses, we will pursue three specific aims: 1) conduct kinome and proteome wide computational profiling studies to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.

项目摘要/摘要 近年来，计算速度已成倍增长。但是，计算ap-的潜力 尚未完全意识到加速药物发现的方法。我们的长期目标是发展和 用于推进基于结构的药物设计的层计算工具。该提议的目的是应用新的 基于尖端分子模拟和量子计算工具的计算协议 激酶的可逆和靶向共价抑制剂（TCI）合理设计中的几个关键主题。 磷酸化的三分之一的蛋白质组和激酶功能失调是调节癌症的主要策略， 自身免疫和炎症状况。近年来，可逆和共价激酶抑制剂正在获得 FDA以快速增长的速度批准。 在我们的新工具开发，试点研究，未发表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目的：1）进行Kinome和蛋白质组广泛的计算研究研究 识别共价目标位置； 2）阐明反应机制和结构可逆关系 用于化学弹头设计； 3）阐明可逆性的选择性和动力学的机制 激酶抑制剂。研究结果将指导当前的TCI发现激酶和 寻找新的可吸毒目标；提供详细的知识，以减轻反应性和可逆性 化学弹头以最大程度地减少毒性；并提供新的策略来提高选择性和动力学参数 可逆抑制剂。成功完成该项目将使我们能够建立一个计算平台 先进的基于结构的药物设计并扩展当前的治疗靶标。