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Nature of the Pre-Chemistry Ensemble in Mitogen-Activated Protein Kinases

机译:在丝裂原激活蛋白激酶中的化学前化学酶的性质

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摘要

In spite of the availability of a significant amount of structural detail on docking interactions involving mitogen-activated protein kinases (MAPKs) and their substrates, the mechanism by which the disordered phospho-acceptor on the substrate transiently interacts with the kinase catalytic elements and is phosphorylated, often with high efficiency, remains poorly understood. Here, this dynamic interaction is analyzed in the context of available biophysical and biochemical data for ERK2, an archetypal MAPK. A hypothesis about the nature of the ternary complex involving a MAPK, its substrate, and ATP immediately prior to the chemical step (the pre-chemistry complex) is proposed. It is postulated that the solution ensemble (the pre-chemistry ensemble) representing the pre-chemistry complex comprises several conformations that are linked by dynamics on multiple timescales. These individual conformations possess different intrinsic abilities to proceed through the chemical step. The overall rate of chemistry is therefore related to the microscopic nature of the pre-chemistry ensemble, its constituent conformational microstates, and their intrinsic abilities to yield a phosphorylated product. While characterizing these microstates within the pre-chemistry ensemble in atomic or near-atomic detail is an extremely challenging proposition, recent developments in hybrid methodologies that employ computational approaches driven by experimental data appear to provide the most promising path forward toward achieving this goal. (C) 2018 Elsevier Ltd. All rights reserved.
机译:尽管结构细节的一个显著量对对接涉及有丝分裂原激活的蛋白激酶(MAPK)和它们的底物,通过该基片上的无序磷酸受体瞬时与相互作用激酶催化元件和机构相互作用的可用性的被磷酸化,往往具有效率高,仍然知之甚少。在此,该动态相互作用在用于ERK2,一个典型的MAPK可用的生物物理和生物化学数据的上下文进行分析。提出关于的三元复合物涉及MAPK的性质,它的底物和ATP之前立即的化学步骤(预化学复合物)甲假说。据推测,该溶液合奏(化学预合奏)表示预化学复合物包含由在多个时间尺度动力学链接几个构象。这些单个的构象具有不同的内在能力,通过进行化学一步。因此化学的总速率与预化学合奏的微观性质,它的组成的构象的微观和其固有的能力,以产生磷酸化产物。虽然表征原子或接近原子的细节预先化学合奏中的这些微观是一个非常具有挑战性的命题,近期混合方法雇用的计算方法由实验数据驱动的发展似乎提供前进的最有前途的路径朝着实现这一目标。 (c)2018年elestvier有限公司保留所有权利。

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