There is an unmet need to classify cancer-promoting kinase mutations in a mechanistically cognizant way. The challenge is to understand how mutations stabilize different kinase configurations to alter function, and how this influences pathogenic potential of the kinase and its responses to therapeutic inhibitors. This goal is made more challenging by the complexity of the mutational landscape of diseases, and is further compounded by the conformational plasticity of each variant where multiple conformations coexist. We focus here on the human MEK1 kinase, a vital component of the RAS/MAPK pathway in which mutations cause cancers and developmental disorders called RASopathies. We sought to explore how these mutations alter the human MEK1 kinase at atomic resolution by utilizing enhanced sampling simulations and free energy calculations. We computationally mapped the different conformational stabilities of individual mutated systems by delineating the free energy landscapes, and showed how this relates directly to experimentally quantified developmental transformation potentials of the mutations. We conclude that mutations leverage variations in the hydrogen bonding network associated with the conformational plasticity to progressively stabilize the active-like conformational state of the kinase while destabilizing the inactive-like state. The mutations alter residue-level internal molecular correlations by differentially prioritizing different conformational states, delineating the various modes of MEK1 activation reminiscent of a gear-shifting mechanism. We define the molecular basis of conversion of this kinase from its inactive to its active state, connecting structure, dynamics, and function by delineating the energy landscape and conformational plasticity, thus augmenting our understanding of MEK1 regulation.

中文翻译：

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激活突变利用齿轮变速机制驱动人类 MEK1 激酶

以机械认知的方式对促癌激酶突变进行分类的需求尚未得到满足。面临的挑战是了解突变如何稳定不同的激酶配置以改变功能，以及这如何影响激酶的致病潜力及其对治疗抑制剂的反应。由于疾病突变环境的复杂性，这一目标变得更具挑战性，并且由于多种构象共存的每个变体的构象可塑性而进一步复杂化。我们在此重点关注人类 MEK1 激酶，它是 RAS/MAPK 通路的重要组成部分，其中突变会导致癌症和称为 RASopathies 的发育障碍。我们试图利用增强的采样模拟和自由能计算来探索这些突变如何在原子分辨率下改变人类 MEK1 激酶。我们通过描绘自由能景观，通过计算绘制了各个突变系统的不同构象稳定性，并展示了这如何与实验量化的突变发育转化潜力直接相关。我们得出的结论是，突变利用与构象可塑性相关的氢键网络的变化来逐渐稳定激酶的活性样构象状态，同时破坏非活性样状态的稳定性。这些突变通过区分不同构象状态的优先顺序来改变残基水平的内部分子相关性，描绘出 MEK1 激活的各种模式，让人想起齿轮变速机制。我们通过描绘能量景观和构象可塑性来定义该激酶从非活性状态转变为活性状态的分子基础，连接结构、动力学和功能，从而增强我们对 MEK1 调控的理解。