Virtual screening studies of the Beta-2 Adrenergic Receptor

Beta-2 肾上腺素受体的虚拟筛选研究

• 批准号: 8067022
• 负责人: Dahlia R Weiss
• 金额: $ 5.13万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-01 至 2013-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8067022
• 关键词: ADRB1 gene; Address; Adrenergic Agonists; Adrenergic Receptor; Adrenergic beta-Antagonists; Affinity; Agonist; Arrestins; Arrhythmia; Asthma; Binding; Binding Sites; Blood Vessels; Cardiovascular system; Cereals; Chemicals; Chronic Obstructive Airway Disease; Collaborations; Computing Methodologies; Crystallography; Data; Databases; Docking; Drug Delivery Systems; Drug Design; Epinephrine; Equilibrium; G-Protein-Coupled Receptors; GTP-Binding Proteins; Hormones; Human; Human body; Hypertension; Lead; Libraries; Ligand Binding; Ligands; Lung; Marketing; Mediating; Membrane Proteins; Methods; Modeling; Molecular; Molecular Conformation; Motion; Nature; Norepinephrine; Pathway interactions; Pharmaceutical Preparations; Physiological; Physiological Processes; Play; Premature Labor; Protein Family; Proteins; Publications; Relaxation; Research; Resolution; Role; Sampling; Screening procedure; Signal Pathway; Signal Transduction; Specificity; Structure; Testing; Therapeutic; Work; base; beta-2 Adrenergic Receptors; drug discovery; flexibility; functional group; gastrointestinal system; inhibitor/antagonist; molecular dynamics; molecular size; novel; public health relevance; receptor; respiratory smooth muscle; scaffold; small molecule libraries; success; virtual

DESCRIPTION (provided by applicant): G-protein coupled receptors (GPCRs), are the largest superfamily of proteins in the human body. As ubiquitous transmembrane receptors, they modulate a vast number of physiological processes. They are the protein family most frequently targeted by drugs, >30% of all marketed therapeutics. Adrenergic receptors are a class of GPCRs that mediate the actions of the hormones adrenaline and noradrenaline. The B2-adrenergic receptor (B2AR) is responsible for the relaxation of vascular, uterine and airway smooth muscle. B1AR antagonists ("beta-blockers") are widely used in cardiovascular therapy for the treatment of angina, arrhythmias, and hypertension. B2AR agonists (activators) are used to treat asthma, COPD and preterm labor. The difficulty of membrane protein x-ray crystallography has severely limited the application of computational structure-based drug discovery against this class of proteins. Recently, the determination of x-ray structures of the human B2AR has provided the first template for rational structure-based drug design. Virtual screening (also called rational drug design or molecular docking) is widely used in drug discovery to extract promising lead compounds from large chemical libraries. Two challenges faced by rational drug design are (1) the treatment of drug target flexibility, often crucial for ligand binding and (2) the efficient sampling of chemical space. We propose to use multi-conformational docking screens to address target flexibility. To generate multiple conformations, we will use two complimentary and distinct computational sampling methods: molecular dynamics, an accurate but computationally expensive method, and normal mode analysis, a coarse-grained but inexpensive method. In previous virtual screens against the B2AR rigid receptor structure, exclusively inverse-agonists (inhibitors) were found, presumably because of bias from the experimental inverse-agonist bound structure. We propose to understand the structural basis of activation through the binding modes of novel activating compounds found in our multi-conformational docking screens. New compounds will be tested experimentally for binding and efficiency. To address chemical space coverage, we will use fragment-based virtual screening. Fragment-based screening focuses on small compounds, smaller than canonical drug leads, with few functional groups. Fragment libraries provide a far greater coverage of chemical space because as molecular size decreases, the number of possible molecules that can be constructed decreases exponentially. As fragment screens uncover new chemical scaffolds, we will look again at top-scoring hits from previous docking screens using larger lead-like molecules to identify additional compounds for further testing. PUBLIC HEALTH RELEVANCE: G-protein coupled receptors (GPCRs), are the largest superfamily of proteins in the human body and the protein family most frequently targeted by drugs, >30% of all marketed therapeutics. We focus on the B2-adrenergic receptor (B2AR), a GPCR that plays a critical role in cardiovascular, pulmonary, uterine and gastrointestinal systems. Pharmacologically, B2AR is a major target in the treatment of asthma, chronic obstructive pulmonary disease (COPD), and preterm labor.

描述（由申请人提供）：G蛋白偶联受体（GPCR）是人体中蛋白质最大的超家族。作为无处不在的跨膜受体，它们调节了大量生理过程。它们是最常被药物靶向的蛋白质家族，占所有销售治疗剂的30％。肾上腺素能受体是一类GPCR，可介导激素肾上腺素和去甲肾上腺素的作用。 B2-肾上腺素能受体（B2AR）负责血管，子宫和气道平滑肌的放松。 B1AR拮抗剂（“β受体阻滞剂”）广泛用于心血管疗法中，用于治疗心绞痛，心律不齐和高血压。 B2AR激动剂（激活剂）用于治疗哮喘，COPD和早产。膜蛋白X射线晶体学的难度严重限制了基于计算结构的药物发现对这类蛋白的应用。最近，人类B2AR的X射线结构的确定为基于理性结构的药物设计提供了第一个模板。虚拟筛查（也称为理性药物设计或分子对接）被广泛用于药物发现中，以从大型化学文库中提取有希望的铅化合物。理性药物设计面临的两个挑战是（1）治疗药物靶标柔韧性，通常对于配体结合至关重要，以及（2）化学空间的有效抽样。我们建议使用多符合的对接屏幕来解决目标灵活性。为了产生多种构象，我们将使用两种免费和独特的计算抽样方法：分子动力学，一种准确但计算昂贵的方法以及正常模式分析，一种粗粒但廉价的方法。在以前针对B2AR刚性受体结构的虚拟筛选中，发现了完全反速变速者（抑制剂），这可能是由于实验性反速度结合结构的偏见。我们建议通过在我们的多构型对接屏幕中发现的新型激活化合物的结合模式来理解激活的结构基础。新化合物将在实验中测试结合和效率。为了解决化学空间覆盖范围，我们将使用基于碎片的虚拟筛选。基于碎片的筛选集中在小型化合物上，比很少的官能团体小的化合物。碎片文库提供了更大的化学空间覆盖范围，因为随着分子大小的减小，可以构造的可能分子的数量呈指数减少。随着片段屏幕发现新的化学支架，我们将再次使用较大的铅样分子来查看以前对接屏幕的最高得分命中，以识别其他化合物以进行进一步测试。 公共卫生相关性：G蛋白偶联受体（GPCR）是人体中蛋白质的最大蛋白质和最常见于药物靶向的蛋白质家族，占所有销售治疗剂的30％。我们专注于B2-肾上腺素能受体（B2AR），GPCR在心血管，肺部，子宫和胃肠道系统中起着至关重要的作用。从药理上讲，B2AR是治疗哮喘，慢性阻塞性肺疾病（COPD）和早产劳动的主要目标。