Structural Determinants of Allosteric Modulation of Brain GPCRs

脑 GPCR 变构调节的结构决定因素

• 批准号: 10450746
• 负责人: Jens Meiler
• 金额: $ 39.6万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10450746
• 关键词: Algorithms; Alzheimer' s Disease; BCL1 Oncogene; Behavior; Benchmarking; Binding; Biological Process; Biology; Brain; Chemicals; Collaborations; Complex; Computer Assisted; Computer Models; Computing Methodologies; Consult; Crystallization; Data; Detection; Development; Disease; Docking; Feedback; Fragile X Syndrome; G-Protein-Coupled Receptors; Generations; Hand; Human; Laboratories; Lead; Libraries; Ligands; Maps; Membrane Proteins; Mental disorders; Metabotropic Glutamate Receptors; Methods; Minor; Modeling; Modification; Molecular Conformation; Muscarinic Acetylcholine Receptor; Mutagenesis; Neurosciences; Parkinson Disease; Pharmaceutical Chemistry; Pharmacology; Research; Sampling; Schizophrenia; Single Nucleotide Polymorphism; Structural Models; Structure; System; Testing; Translating; addiction; base; comparative; design; drug discovery; experience; improved; in silico; innovation; lead optimization; metabotropic glutamate receptor 3; metabotropic glutamate receptor 4; mutant; nervous system disorder; new technology; novel; patient population; pharmacophore; predictive modeling; programs; receptor; receptor function; scaffold; simulation; small molecule; therapeutic development; therapeutic target; treatment strategy

SUMMARY Modulators of G-Protein Coupled Receptors (GPCRs) in the human brain have a potential for development of novel treatment strategies targeting neurological disorders such as schizophrenia, Parkinson’s disease, Alzheimer’s disease, and fragile X syndrome/autism. Over the past years more than 10,000 compounds have been identified that interact with muscarinic receptor (mAChRs) and metabotropic glutamate receptor (mGluRs) GPCRs, often allosteri- cally modulating the receptor. Varying pharmacological effects are observed depending on which of several receptor subtypes is engaged and whether the compound is a Positive or Negative Allosteric Modulator (PAM/NAM). The picture is complicated by a number of non-synonymous Single Nucleotide Polymorphisms (nsSNPs) in these recep- tors that are observed in patient populations. It becomes critical to understand when and how a modulator engages the disease mutant receptor as a seemingly minor modification on a scaffold or ‘chemotype’ may shift selectivity or cause a ‘mode switch’ between PAM and NAM. However, it is currently not possible to predict how a structural change of the ligand translates into a shift in its pharmacology. It is the central hypothesis of this proposal that a chemotype has an intrinsic ability to bind to a certain allosteric binding pocket in a conserved binding mode and chemical modification on this chemotype dictates selectivity, activity with respect to mutant receptors, or PAM versus NAM activity. With the recently determined experimental structures of both mGluR and mAChR in complex with allosteric modulators we can test this hypothesis. In combination with the breadth and depth of chemical space of known allosteric modulators, it is the objective of this proposal to develop Quantitative Structure-Activity Relation (QSAR) models of allosteric modulation of brain GPCRs. To leverage co-crystal structures as well as small molecule SAR for the construction of such models this proposal develops innovative computational methods that integrate ligand-based (LB) and structure-based (SB) computer aided drug discovery (CADD) methods. I will map QSAR models onto structural models of the allosteric modulator in complex with the GPCR and so highlight the structural determinants of activity. Selected ligands will be co-crystallized with the receptor to critically evaluate and ultimately confirm the computational modeling approaches and facilitate CADD. In collaboration, I will demonstrate that such models spur the development of lead and probe compounds with tailored pharmacological profiles that help study the biological function of these receptors. Compu- tational models will be confirmed in an iterative feedback loop through mutagenesis studies and co-crystallization through collaboration partners. Ultimately, they will become starting points for a second generation of allosteric mod- ulators with the mode of action that is understood at atomic level of detail.

概括 人脑中G蛋白偶联受体（GPCR）的调节剂具有发展的潜力 针对神经系统疾病的新型治疗策略，例如精神分裂症，帕金森氏病，阿尔茨海默氏病 疾病和脆弱的X综合症/自闭症。在过去的几年中，已经确定了10,000多种化合物 与毒蕈碱受体（MACHR）和代谢型谷氨酸受体（MGLURS）GPCR相互作用，通常是变构 调用调节受体。根据几个受体中的哪个观察到不同的药物效应 亚型参与，该化合物是阳性还是负变构调节剂（PAM/NAM）。这 在这些接受中，许多非同义单核苷酸多态性（NSSNP）使图片复杂化。 在患者人群中观察到的TOR。了解调制器何时以及如何参与 疾病突变受体是在支架或“化学型”上看似较小的修饰，可能会改变选择性或 在PAM和NAM之间引起“模式开关”。但是，目前无法预测结构性变化 配体的药理学转变。 该提议的核心假设是，化学型具有与某个特定结合的内在能力 在保守的结合模式下的变构结合袋，并且在这种化学型上进行化学修饰决定了 选择性，相对于突变接收器的活性，或PAM与NAM活性。与最近确定的 Mglur和MACHR的实验结构与变构调节剂复杂化，我们可以检验该假设。 结合已知变构调节剂的化学空间的宽度和深度，它是目的 这项提出了开发定量结构 - 活性关系（QSAR）模型的建议。 脑GPCR。利用共晶结构以及小分子SAR来构建此类模型 该提案开发了创新的计算方法，该方法整合了基于配体的（LB）和基于结构的（SB） 计算机辅助药物发现（CADD）方法。我将QSAR模型映射到变构的结构模型 与GPCR复杂的调节器，因此强调了活动的结构决定者。选定的配体将是 与接收器共结晶，以批判性评估并最终确认计算建模方法 并促进CADD。在合作中，我将证明这种模型刺激了铅的发展并证明 具有量身定制的药物特征的化合物，有助于研究这些受体的生物学功能。组成 通过诱变研究和共结晶将在迭代反馈回路中确认倾向模型 通过合作伙伴。最终，它们将成为第二代变构模式的起点 以原子级别的细节层面理解的作用方式。