Computer-assisted identification and design of subtype selective GPCR antagonist

亚型选择性GPCR拮抗剂的计算机辅助鉴定和设计

• 批准号: 7670950
• 负责人: Maxim Totrov
• 金额: $ 25万
• 依托单位: MOLSOFT, LLC
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-17 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7670950
• 关键词: Academia; Accounting; Adrenergic Agents; Adrenergic Receptor; Adverse effects; Affinity; Agonist; Amines; Arts; Benchmarking; Binding; Biochemical; Biogenic Amines; Biological Assay; Biological Sciences; Cardiovascular system; Chemicals; Clinical; Collaborations; Complex; Computer Assisted; Computer Simulation; Contracts; Data; Data Set; Development; Docking; Dopamine; Dopamine Receptor; Drug Design; Drug Industry; Family; Fostering; G Protein-Coupled Receptor Genes; G-Protein-Coupled Receptors; Goals; Homology Modeling; Hot Spot; Housing; Individual; Lead; Libraries; Ligand Binding; Ligands; Measures; Mental disorders; Modeling; Modification; Molecular Models; Neuraxis; Neurodegenerative Disorders; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Procedures; Proteins; Receptor Activation; Resolution; Rhodopsin; Safety; Screening Result; Screening procedure; Serotonin; Side; Specificity; Structural Models; Structure; Testing; Therapeutic; Time; Validation; Vendor; Vertebral column; adrenergic; analog; base; blind; carazolol; computerized tools; cost; cross reactivity; design; drug candidate; flexibility; improved; molecular modeling; monoamine; novel; programs; public health relevance; receptor; receptor binding; scaffold; success; therapy development; three-dimensional modeling; tool; virtual

DESCRIPTION (provided by applicant): The identification and design of highly selective agonists and antagonists for CNS-related G coupled protein receptors (GPCRs) is of paramount importance for the development of new drugs to well-known GPCR targets and for the clinical validation of new targets for a wide range of mental disorders. The long term goal of our project is to capitalize on the recent breakthroughs in GPCR crystal structure determination and to use advanced molecular modeling to create and validate an efficient in silico GPCR ligand affinity/selectivity profiling panel (GLASP panel) for applications to the computer assisted rational design of subtype selective drug candidates. In year one of Phase I, we plan to develop and validate the GLASP panel for amine binding families of CNS-related GPCR targets with the closest structural and functional homology to the recently solved b2-adrenergic (b2AR) high resolution 3D template. We will build detailed all-atom models of all GPCR subtypes in adrenergic, serotonin and dopamine families, taking into account conformational flexibility and ligand-induced plasticity of receptors. The individual models and the whole affinity/selectivity panel will be optimized and verified with a comprehensive set of publicly available ligand affinity data. In addition, we plan to strictly validate the GLASP panel though blind prediction of affinity for a selected set of ligands, followed by biochemical testing and assessment of the panel accuracy by a third party. In year two, we plan to employ the validated in silico profiling panel in several rational drug design applications. Thus, we will use these tools to perform computer assisted lead optimization for targets selected by our partners in pharmaceutical industry. In addition, simplified versions of the all-atom models will be prepared and validated for fast virtual ligand screening (VLS) applications. The VLS models will be used to search large libraries of available and virtual compounds, and a selected focused library will be screened in biochemical assays to identify new lead candidates. The validated GLASP panel and fast VLS models will provide powerful tools for the cost-efficient rational design of novel high-affinity scaffolds and subtype selective agonists and antagonists for clinically important GPCR targets. Upon success of the Phase I project, we envision further extension of this approach to other CNS-related Class A GPCRs, and application to a number of collaborative programs in pharmaceutical industry and academia. PUBLIC HEALTH RELEVANCE: About half of the medications for mental disorders and neurodegenerative diseases target G-coupled Protein Receptors (GPCRs), but many of these drugs have serious side effects through "off target" activity with other GPCRs in the central nervous system (CNS) or the cardiovascular system. Improvement of existing treatments and development of new treatments for CNS targets depend on the design of highly selective molecules acting on one specific GPCR subtype. Recent breakthrough developments in GPCR atomic structure determination and improved molecular modeling tools make it possible to create and validate efficient applications for computer assisted rational design of new candidate drugs, which is the prime goal of our project.

描述（由申请人提供）：CNS相关G偶联蛋白受体（GPCR）的高选择性激动剂和拮抗剂的鉴定和设计对于开发针对已知GPCR靶点的新药以及对各种精神疾病的新靶点进行临床验证至关重要。本项目的长期目标是利用GPCR晶体结构测定的最新突破，并使用先进的分子建模来创建和验证有效的计算机GPCR配体亲和力/选择性分析面板（GLASP面板），以应用于亚型选择性候选药物的计算机辅助合理设计。在第一阶段的第一年，我们计划开发和验证CNS相关GPCR靶标的胺结合家族的GLASP面板，其与最近解决的b2-肾上腺素能（b2 AR）高分辨率3D模板具有最接近的结构和功能同源性。我们将建立详细的所有GPCR亚型的肾上腺素，5-羟色胺和多巴胺的家庭，考虑到构象的灵活性和配体诱导的可塑性受体的全原子模型。单个模型和整个亲和力/选择性面板将使用一组全面的公开可用配体亲和力数据进行优化和验证。此外，我们计划通过盲法预测所选配体的亲和力来严格验证GLASP组，然后由第三方进行生化测试和评估组的准确性。在第二年，我们计划在几个合理的药物设计应用中使用经过验证的计算机分析面板。因此，我们将使用这些工具来执行计算机辅助铅优化的目标选择我们的合作伙伴在制药行业。此外，简化版本的全原子模型将准备和验证快速虚拟配体筛选（VLS）的应用。VLS模型将用于搜索可用和虚拟化合物的大型库，并将在生物化学测定中筛选选定的重点库，以确定新的先导候选物。经验证的GLASP面板和快速VLS模型将为具有成本效益的合理设计新型高亲和力支架和亚型选择性激动剂和拮抗剂提供强大的工具，用于临床重要的GPCR靶点。在第一阶段项目成功后，我们设想将这种方法进一步扩展到其他CNS相关的A类GPCR，并应用于制药行业和学术界的许多合作项目。公共卫生相关性：大约一半的精神障碍和神经退行性疾病药物靶向G偶联蛋白受体（GPCR），但这些药物中的许多药物通过与中枢神经系统（CNS）或心血管系统中的其他GPCR的“脱靶”活性而具有严重的副作用。改善现有的治疗和开发新的治疗中枢神经系统的目标取决于设计的高度选择性分子作用于一个特定的GPCR亚型。最近在GPCR原子结构测定和改进的分子建模工具方面的突破性发展使得有可能创建和验证新候选药物的计算机辅助合理设计的有效应用，这是我们项目的主要目标。