Assessment of Conformational State Transitions of Class B GPCRs Using Molecular Dynamics.
Assessment of Conformational State Transitions of Class B GPCRs Using Molecular Dynamics.
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DOI：
10.1007/978-1-4939-9121-1_1
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发表时间：
2019
影响因子：
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通讯作者：
Chenyi Liao;V. May;Jianing Li
中科院分区：
文献类型：
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作者：
Chenyi Liao;V. May;Jianing Li
B类G蛋白偶联受体（gpcr）由15个肽结合成员组成，是内分泌、代谢和应激相关疾病的关键靶点。虽然它们的蛋白质结构和动力学在很大程度上仍不清楚，但计算机建模和模拟代表了一种有希望的方法来帮助解决这些难题。在此，我们介绍了分子动力学（MD）模拟的基本方法和两种分析方法来评估B类gpcr的构象集成和转变，以我们最近对人垂体腺苷酸环化酶激活多肽（PAC1）受体的研究为例。通过长时间的MD模拟，研究人员对在配体结合和受体激活中具有不同作用的构象集合进行了采样，以确定pac1受体的“开放”或“关闭”四种状态。接下来，动态网络可以用于分析模拟并识别每个构象集合中的关键特征，这些特征有助于区分pac1受体的配体结合状态和无配体状态。此外，马尔可夫状态模型已经成为构建转移网络和连接GPCR集合的关键方法，为转移途径和动力学提供了详细的信息。对于无配体的pac1受体，闭合状态内的转变比开闭状态快近10-30倍，这可能与受体的激活机制有关。总的来说，长分子量模拟和分析有助于评估B类gpcr的构象转变，并获得其他方法难以获得的机制见解。
Class B G protein-coupled receptors (GPCRs) comprise a family of 15 peptide-binding members, which are crucial targets for endocrine, metabolic, and stress-related disorders. While their protein structures and dynamics remain largely unclear, computer modeling and simulations represent a promising means to help solve such puzzles. Herein, we present a basic introduction to the methodology of molecular dynamics (MD) simulations and two analytical methods to assess the conformational ensembles and transitions of Class B GPCRs, using our recent studies of the human pituitary adenylate cyclase activating polypeptide (PAC1) receptor as an example. From long MD simulations, conformational ensembles with different roles in ligand binding and receptor activation are sampled to establish four states identified as either “open” or “closed” for the PAC1receptor. Next, the dynamical network can be applied to analyze the simulations and identify key features within each conformational ensemble, which help distinguish the ligand-bound states of the PAC1receptor from the ligand-free one. Further, the Markov State Model has emerged as a key approach to construct the transition network and connect the GPCR ensembles, providing detailed information for the transition pathways and kinetics. For the ligand-free PAC1receptor, the transitions within the closed states are near 10–30 times faster than the open-closed transitions, which is likely related to the activation mechanism of the receptor. Overall, long MD simulations and analyses are useful to assess conformational transitions for the Class B GPCRs and to gain mechanistic insight, which is difficult to obtain using other methods.