Virtual screening studies of the Beta-2 Adrenergic Receptor

Beta-2 肾上腺素受体的虚拟筛选研究

基本信息

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
项目类别：
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

项目摘要

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）是人体内最大的蛋白质超家族。作为普遍存在的跨膜受体，它们调节大量的生理过程。它们是最常被药物靶向的蛋白质家族，占所有上市治疗药物的 30% 以上。肾上腺素受体是一类介导肾上腺素和去甲肾上腺素激素作用的 GPCR。 B2 肾上腺素能受体 (B2AR) 负责血管、子宫和气道平滑肌的松弛。 B1AR拮抗剂（“β受体阻滞剂”）广泛用于心血管治疗，用于治疗心绞痛、心律失常和高血压。 B2AR 激动剂（激活剂）用于治疗哮喘、慢性阻塞性肺病和早产。膜蛋白 X 射线晶体学的困难严重限制了针对此类蛋白质的基于计算结构的药物发现的应用。最近，人类 B2AR X 射线结构的确定为基于合理结构的药物设计提供了第一个模板。虚拟筛选（也称为合理药物设计或分子对接）广泛用于药物发现，从大型化学库中提取有前途的先导化合物。合理药物设计面临的两个挑战是（1）药物靶点灵活性的处理，这通常对于配体结合至关重要；（2）化学空间的有效采样。我们建议使用多构象对接屏幕来解决目标灵活性。为了生成多种构象，我们将使用两种互补且不同的计算采样方法：分子动力学（一种准确但计算成本昂贵的方法）和正态模式分析（一种粗粒度但廉价的方法）。在之前针对 B2AR 刚性受体结构的虚拟筛选中，仅发现了反向激动剂（抑制剂），这可能是由于实验反向激动剂结合结构的偏差。我们建议通过在多构象对接屏幕中发现的新型激活化合物的结合模式来了解激活的结构基础。新化合物将通过实验测试其结合力和效率。为了解决化学空间覆盖问题，我们将使用基于片段的虚拟筛选。基于片段的筛选侧重于比典型药物先导物更小的化合物，且具有很少的官能团。片段库提供了更大的化学空间覆盖范围，因为随着分子尺寸的减小，可以构建的可能分子的数量呈指数减少。随着片段筛选发现新的化学支架，我们将再次查看先前对接筛选的最高得分命中，使用更大的类铅分子来识别其他化合物以进行进一步测试。公共健康相关性：G 蛋白偶联受体 (GPCR) 是人体内最大的蛋白质超家族，也是最常被药物靶向的蛋白质家族，占所有上市治疗药物的 30% 以上。我们重点关注 B2 肾上腺素能受体 (B2AR)，这是一种在心血管、肺、子宫和胃肠系统中发挥关键作用的 GPCR。从药理学角度来看，B2AR 是治疗哮喘、慢性阻塞性肺病 (COPD) 和早产的主要靶点。