Structural Determinants of Allosteric Modulation of Brain GPCRs

摘要 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型治疗策略 疾病和脆性 X 综合征/自闭症。在过去的几年里，已经鉴定出 10,000 多种化合物 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 调节受体。根据几种受体的不同，观察到不同的药理作用 涉及的亚型以及该化合物是正变构调节剂还是负变构调节剂 (PAM/NAM)。的 这些受体中的许多非同义单核苷酸多态性（nsSNP）使情况变得复杂 在患者群体中观察到的扭曲。了解调制器何时以及如何参与变得至关重要 疾病突变受体作为支架或“化学型”上看似微小的修饰可能会改变选择性或 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将如何发生。 配体的改变转化为其药理学的转变。 该提案的中心假设是化学型具有与特定物质结合的内在能力。 保守结合模式的变构结合口袋和该化学型的化学修饰决定了 选择性、针对突变受体的活性或 PAM 与 NAM 活性。随着最近确定的 通过 mGluR 和 mAChR 与变构调节剂复合物的实验结构，我们可以检验这一假设。 结合已知变构调节剂化学空间的广度和深度，目标是 该提案旨在开发变构调节的定量构效关系（QSAR）模型 大脑 GPCR。利用共晶结构和小分子 SAR 构建此类模型 该提案开发了集成基于配体（LB）和基于结构（SB）的创新计算方法 计算机辅助药物发现（CADD）方法。我将把 QSAR 模型映射到变构结构模型上 调节剂与 GPCR 形成复合物，因此突出了活性的结构决定因素。选定的配体将是 与受体共结晶，以严格评估并最终确认计算建模方法 并促进 CADD。在合作中，我将证明此类模型可以刺激先导和探针的发展 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。计算机- 国家模型将通过诱变研究和共结晶在迭代反馈循环中得到确认 通过合作伙伴。最终，它们将成为第二代变构模型的起点 具有可在原子级细节上理解的作用模式的调节器。

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.