Keck Center for Science and Engineering, Graduate Program in Computational and Data Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, USA.
Department of Chemistry, Center for Research Computing, Center for Drug Discovery, Design, and Delivery (CD4), Southern Methodist University, Dallas, Texas 75205, USA.
J Chem Phys. 2022 Dec 28;157(24):245101. doi: 10.1063/5.0133826.
In the current study, multiscale simulation approaches and dynamic network methods are employed to examine the dynamic and energetic details of conformational landscapes and allosteric interactions in the ABL kinase domain that determine the kinase functions. Using a plethora of synergistic computational approaches, we elucidate how conformational transitions between the active and inactive ABL states can employ allosteric regulatory switches to modulate intramolecular communication networks between the ATP site, the substrate binding region, and the allosteric binding pocket. A perturbation-based network approach that implements mutational profiling of allosteric residue propensities and communications in the ABL states is proposed. Consistent with biophysical experiments, the results reveal functionally significant shifts of the allosteric interaction networks in which preferential communication paths between the ATP binding site and substrate regions in the active ABL state become suppressed in the closed inactive ABL form, which in turn features favorable allosteric coupling between the ATP site and the allosteric binding pocket. By integrating the results of atomistic simulations with dimensionality reduction methods and Markov state models, we analyze the mechanistic role of macrostates and characterize kinetic transitions between the ABL conformational states. Using network-based mutational scanning of allosteric residue propensities, this study provides a comprehensive computational analysis of long-range communications in the ABL kinase domain and identifies conserved regulatory hotspots that modulate kinase activity and allosteric crosstalk between the allosteric pocket, ATP binding site, and substrate binding regions.
在当前的研究中,采用多尺度模拟方法和动态网络方法来研究 ABL 激酶结构域构象景观和变构相互作用的动态和能量细节,这些构象景观和变构相互作用决定了激酶的功能。使用大量协同的计算方法,我们阐明了活性和非活性 ABL 状态之间的构象转变如何利用变构调节开关来调节 ATP 结合位点、底物结合区域和变构结合口袋之间的分子内通讯网络。提出了一种基于扰动的网络方法,该方法对 ABL 状态下变构残基倾向和通讯进行突变分析。与生物物理实验一致的是,结果揭示了变构相互作用网络中功能显著的转变,其中在活性 ABL 状态下 ATP 结合位点和底物区域之间的优先通讯路径在封闭的非活性 ABL 形式中受到抑制,而在这种形式中,ATP 结合位点和变构结合口袋之间则呈现出有利的变构偶联。通过将原子模拟的结果与降维方法和 Markov 状态模型相结合,我们分析了 ABL 构象状态之间的动力学转变的宏观状态的机械作用。通过对变构残基倾向进行基于网络的突变扫描,本研究对 ABL 激酶结构域中的长程通讯进行了全面的计算分析,并确定了调节激酶活性和变构口袋、ATP 结合位点和底物结合区域之间的变构串扰的保守调节热点。