Structural Determinants of Allosteric Modulation of Brain GPCRs

脑 GPCR 变构调节的结构决定因素

• 批准号: 10207579
• 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/10207579
• 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.

总结 人脑中G蛋白偶联受体（GPCR）的调节剂具有开发 针对精神分裂症、帕金森病、阿尔茨海默病等神经系统疾病的新治疗策略 脆性X综合征/自闭症。在过去的几年里，已经鉴定出超过10，000种化合物， 与毒蕈碱受体（mAChRs）和代谢型谷氨酸受体（mGluRs）GPCR相互作用，通常是变构的， cally调节the receptor受体.根据几种受体中的哪一种， 亚型参与以及化合物是正变构调节剂还是负变构调节剂（PAM/NAM）。的 图片是复杂的一些非同义单核苷酸多态性（nsSNPs）在这些受体， 在患者人群中观察到的。了解调制器何时以及如何与 疾病突变体受体作为支架或“化学型”上表面上的微小修饰可以改变选择性， 导致PAM和NAM之间的“模式切换”。然而，目前还无法预测结构性变化是如何发生的。 转化为药理学上的转变。 这是该提议的核心假设，即化学型具有与特定的 保守结合模式的变构结合口袋和对该化学型的化学修饰决定了 选择性，相对于突变受体的活性，或PAM对NAM活性。随着最近确定的 mGluR和mAChR与变构调节剂复合物的实验结构我们可以验证这一假设。 结合已知的变构调节剂的化学空间的广度和深度，本发明的目的在于： 该建议旨在建立变构调节的定量构效关系（QSAR）模型， 脑GPCR。利用共晶结构以及小分子SAR构建此类模型 该提案开发了创新的计算方法，将基于配体（LB）和基于结构（SB）的计算方法结合起来 计算机辅助药物发现（CADD）。我将把QSAR模型映射到变构的结构模型上， 调节剂与GPCR复合，因此突出了活性的结构决定因素。选择的配体将是 与受体共结晶，以严格评估并最终确认计算建模方法 ，以方便CADD。在合作中，我将证明这种模型刺激铅和探针的发展 具有定制药理学特征的化合物，有助于研究这些受体的生物学功能。化合物 通过诱变研究和共结晶， 通过合作伙伴。最终，它们将成为第二代变构模型的起点， 具有在原子级细节上理解的作用模式的机器人。