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Src 激酶构象失活的全原子自适应偏置路径优化:αC 螺旋和激活环协同运动中的切换静电网络。

All-atom adaptively biased path optimization of Src kinase conformational inactivation: Switched electrostatic network in the concerted motion of αC helix and the activation loop.

机构信息

Department of Medicinal Chemistry and Molecular Pharmacology, Markey Center for Structural Biology, Purdue Center for Cancer Research, Purdue University, West Lafayette, Indiana 47907, USA.

出版信息

J Chem Phys. 2020 Nov 7;153(17):175101. doi: 10.1063/5.0021603.

Abstract

A method to optimize a conformational pathway through a space of well-chosen reduced variables is employed to advance our understanding of protein conformational equilibrium. The adaptively biased path optimization strategy utilizes unrestricted, enhanced sampling in the region of a path in the reduced-variable space to identify a broad path between two stable end-states. Application to the inactivation transition of the Src tyrosine kinase catalytic domain reveals new insight into this well studied conformational equilibrium. The mechanistic description gained from identifying the motions and structural features along the path includes details of the switched electrostatic network found to underpin the transition. The free energy barrier along the path results from rotation of a helix, αC, that is tightly correlated with motions in the activation loop (A-loop) as well as distal regions in the C-lobe. Path profiles of the reduced variables clearly demonstrate the strongly correlated motions. The exchange of electrostatic interactions among residues in the network is key to these interdependent motions. In addition, the increased resolution from an all-atom model in defining the path shows multiple components for the A-loop motion and that different parts of the A-loop contribute throughout the length of the path.

摘要

采用了一种通过精心选择的约简变量空间优化构象途径的方法,以增进我们对蛋白质构象平衡的理解。自适应偏置路径优化策略利用无约束的、增强的采样,在约简变量空间中的路径区域,来识别两个稳定末端状态之间的广泛路径。该方法应用于Src 酪氨酸激酶催化结构域的失活转变,揭示了对此经过深入研究的构象平衡的新见解。通过识别沿路径的运动和结构特征,可以获得关于这种转变的机制描述,其中包括发现支撑转变的开关静电网络的细节。沿路径的自由能势垒来自于一个螺旋,αC 的旋转,这与激活环(A 环)以及 C 结构域的远端区域的运动紧密相关。约简变量的路径分布清楚地表明了强烈相关的运动。网络中残基之间的静电相互作用的交换是这些相互依存的运动的关键。此外,从全原子模型中对路径进行的更高分辨率定义表明,A 环的运动具有多个成分,并且 A 环的不同部分在整个路径长度上都有贡献。

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