Structural Determinants of Allosteric Modulation of Brain GPCRs

摘要 人脑中G蛋白偶联受体(GPCRs)的调节剂有可能发展为 针对精神分裂症、帕金森氏病、阿尔茨海默氏症等神经疾病的新治疗策略 疾病和脆性X综合征/自闭症。在过去的几年里，超过10,000种化合物被鉴定出来 与M受体(MAChRs)和代谢性谷氨酸受体(MGluRs)GPCRs相互作用，通常是变构- CALLY调节受体。观察到不同的药理作用取决于几种受体中的哪一种 亚型以及化合物是正变构调节剂还是负变构调节剂(PAM/NAM)。这个 在这些受体中，许多非同义单核苷酸多态(NsSNPs)使情况变得复杂。 在患者群体中观察到的TORS。了解调制器何时以及如何接合变得至关重要 疾病突变受体作为支架或化学类型上看似很小的修饰，可能会改变选择性或 在PAM和NAM之间进行模式切换。然而，目前还不可能预测结构性变化如何 配体的变化转化为它的药理作用的转变。 这一建议的中心假设是，化学类型具有与某个特定的 变构结合口袋处于保守的结合模式，对这种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与NAM的活性。与最近确定的 MGluR和mAChR在含有变构调节剂的络合物中的实验结构我们可以验证这一假说。 结合已知变构调节剂的化学空间的广度和深度，它的目标是 提出了建立变构调控的定量构效关系模型的建议。 脑GPCR。利用共晶结构和小分子合成孔径雷达构建这样的模型 这一建议开发了基于配体(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模型映射到变构的结构模型上 调节剂在与GPCR的复合体中突出活性的结构决定因素。选定的配体将是 与受体共结晶以批判性地评估并最终确认计算建模方法 并为CADD提供便利。在合作中，我将展示这些模型促进了Lead和Probe的发展 具有量身定做的药理特征的化合物，有助于研究这些受体的生物功能。计算机- 计算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 通过协作合作伙伴。最终，它们将成为第二代变构模式的起点- 吹毛求疵者具有在原子细节水平上被理解的行动模式。

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.