Development of computational models to understand the dynamic molecular recognition mechanisms of cannabinoid receptors

开发计算模型以了解大麻素受体的动态分子识别机制

• 批准号: RGPIN-2021-03161
• 负责人: Ganesan, Aravindhan
• 金额: $ 2.7万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=762147
• 关键词: Development; computational; models; understand; dynamic

Background: The use of cannabis has been legalized for both recreational and medical purposes in several countries worldwide including Canada. The latest data from Health Canada show that there were 329,038 active medical cannabis registrations during the first quarter of 2020. While the benefits of cannabis have been widely agreed, it is vital to enhance our understanding about the molecular mechanisms of how cannabinoids (CBs) - the active chemicals in cannabis- mediate their effects, which will help to develop safer and psychoactivity-free CBs. CBs are known to modulate the cannabinoid receptors (CBRs), CB1 and CB2, in humans. CB1 is expressed in the central nervous system, whereas the CB2 is mainly found in the immune system. The activation of these receptors by the binding of endogenous or exogenous CBs triggers a cascade of signaling pathways that is important for diverse physiological roles such as feeding, pain, emotional behaviour, immunity and lipid metabolism. Therefore, CB1 and CB2 have emerged as important class of enzymes. In the past decade, several synthetic and plant-based CBs have been developed. But, the modulation of CB1 in the leads to psychoactivity. On the contrary, since CB2 expression is concentrated in the immune system, and to a lesser extent in the brain, psychoactive side-effects can be evaded by regulating CB2. However, most of the known CBs non-specifically bind to both CB1 and CB2 and caused mild to severe psychoactivity. Therefore, it is crucial to identify molecular features that are unique to the two cannabinoid receptors to develop isoform-selective molecules. In addition, there remain numerous questions about the structural plasticity, ligand interactions, activation and signalling processes in cannabinoid receptors, which we seek to address in this research program. Objectives and methods: This research program aims at revealing molecular level details that are critical for isoform specificity in CBRs. Our objectives are to (O1) build comprehensive dynamical atomistic models of cannabinoid receptors, (O2) characterize the ligand-CB receptor interactions to elucidate the molecular processes behind ligand-mediated modulation of the cannabinoid receptors, and (O3) model specific protein-protein interactions that promote CBR signaling. We will use a combination of advanced computational modelling, molecular dynamics simulation approaches, machine learning methods and complementary experimental techniques to achieve our objectives. Impact: This research will contribute original knowledge in bioscience, chemical biology and train HQP by advancing our fundamental knowledge linked with mechanistic processes of molecular recognition in CBRs. Such insights could be useful to develop selective CBs without psychoactivity. The program will also be a suitable platform for training next generation of scientists in molecular modelling-driven endocannabinoid research.

背景：在包括加拿大在内的世界上一些国家，用于娱乐和医疗目的的大麻使用已合法化。加拿大卫生部的最新数据显示，2020年第一季度，有329,038名活跃的医用大麻注册。虽然大麻的好处已得到广泛认同，但加强我们对大麻素（大麻中的活性化学物质）如何调节其作用的分子机制的理解至关重要，这将有助于开发更安全、无精神活动的大麻素。众所周知，CBs可以调节人体中的大麻素受体（CB1和CB2）。CB1在中枢神经系统表达，而CB2主要存在于免疫系统。内源性或外源性CBs结合激活这些受体，触发一系列信号通路，这些信号通路对多种生理作用（如进食、疼痛、情绪行为、免疫和脂质代谢）非常重要。因此，CB1和CB2已成为一类重要的酶。在过去的十年中，已经开发了几种合成的和基于植物的CBs。但是，CB1的调节会导致精神活动。相反，由于CB2的表达主要集中在免疫系统中，在较小程度上集中在大脑中，因此可以通过调节CB2来避免精神活性副作用。然而，大多数已知的CBs非特异性结合CB1和CB2，并引起轻度至重度精神活动。因此，确定两种大麻素受体独特的分子特征以开发同种异构体选择性分子至关重要。此外，关于大麻素受体的结构可塑性，配体相互作用，激活和信号传导过程仍然存在许多问题，我们在本研究计划中寻求解决。目的和方法：本研究项目旨在揭示对cbr同种异构体特异性至关重要的分子水平细节。我们的目标是（O1）建立大麻素受体的综合动态原子模型，（O2）表征配体- cb受体相互作用，以阐明配体介导的大麻素受体调节背后的分子过程，以及（O3）模型促进CBR信号传导的特异性蛋白质-蛋白质相互作用。我们将结合先进的计算建模、分子动力学模拟方法、机器学习方法和互补的实验技术来实现我们的目标。影响：本研究将在生物科学、化学生物学和HQP方面贡献原创知识，通过推进我们与cbr分子识别机制过程相关的基础知识来培养HQP。这些见解可能有助于开发没有精神活动的选择性CBs。该项目还将成为培训下一代科学家从事分子模型驱动的内源性大麻素研究的合适平台。