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Biophysics  2024 

基于弹性网络模型和微扰响应扫描的PKC-θ的动力学和关键残基研究
Study on the Dynamics and Key Residues of PKC-θ Based on Elastic Network Model and Perturbation Response Scanning

DOI: 10.12677/biphy.2024.124006, PP. 51-59

Keywords: PKC-θ,弹性网络模型,微扰响应扫描,动力学
PKC-θ
, Elastic Network Model, Perturbation Response Scanning, Dynamics

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Abstract:

PKC-θ (protein kinase C-theta)激酶能够对底物蛋白中的丝氨酸/苏氨酸进行磷酸化修饰,并参与T细胞活化、信号转导及免疫应答等重要生理过程,与许多免疫疾病相关,因此研究PKC-θ的结构动力学及其关键位点具有重要意义。在本工作中,我们对PKC-θ构建了弹性网络模型,并在慢运动模式下识别出了结构中重要的功能区域。通过残基的运动相关性分析发现:N端小叶和C端大叶的运动是负相关的,这一致于两叶间的“开合运动”,有助于结合配体的稳定;此外,催化相关残基与DFG基序的运动呈正相关,这有利于催化功能的发挥。接着,利用微扰响应扫描方法来识别变构关键残基,结果发现,高敏感性残基对配体结合及酶的催化活性很重要。这项工作有助于加强对PKC-θ结构动力学的理解,并为设计激酶抑制剂提供重要信息。
PKC-θ (Protein Kinase C-theta) can phosphorylate the serine/threonine of substrate protein, participating in important physiological processes such as T cell activation, signal transduction and immune response, and related to many immune diseases. Thus, it is of great significance to study its structural dynamics and key residues. In this work, we construct PKC-θ’s elastic network model, and the important functional areas are identified based on GNM’s slow motion modes. According to interresiduemotion correlations, it is found that there exists a negative motion correlation between N-lobe and C-lobe, consistent with their open-closed motion, which helps for the bound ligand’s stability; in addition, there is a positive motion correlation between DFG motif and catalysis related residues, which is conducive to the catalytic function exertion. Then, the perturbation response scanning method is used to identify the key residues for allostery, and the results suggest that the key residues of high sensitivity are important for ligand binding and enzyme’s catalytic activity. This work helps to strengthen the understanding of structural dynamics of PKC-θ and provides important information for kinase inhibitor design.

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