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Hybrid Dynamics Simulation Engine for Metalloproteins

机译:金属蛋白的混合动力学仿真引擎

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摘要

Quality computational description of metalloproteins is a great challenge due to the vast span of time- and lengthscales characteristic of their existence. We present an efficient new method that allows for robust characterization of metalloproteins. It combines quantum mechanical (QM) description of the metal-containing active site, and extensive dynamics of the protein captured by discrete molecular dynamics (DMD) (QM/DMD). DMD samples the entire protein, including the backbone, and most of the active site, except for the immediate coordination region of the metal. QM operates on the part of the protein of electronic and chemical significance, which may include tens to hundreds of atoms. The breathing quantum-classical boundary provides a continuous mutual feedback between the two machineries. We test QM/DMD using the Fe-containing electron transporter protein, rubredoxin, and its three mutants as a model. QM/DMD can provide a reliable balanced description of metalloproteins’ structure, dynamics, and electronic structure in a reasonable amount of time. As an illustration of QM/DMD capabilities, we then predict the structure of the Ca2+ form of the enzyme catechol O-methyl transferase, which, unlike the native Mg2+ form, is catalytically inactive. The Mg2+ site is ochtahedral, but the Ca2+ is 7-coordinate and features the misalignment of the reacting parts of the system. The change is facilitated by the backbone adjustment. QM/DMD is ideal and fast for providing this level of structural insight.
机译:金属蛋白的质量计算描述由于其存在的时间和长度尺度的巨大跨度而面临巨大挑战。我们提出了一种有效的新方法,可以对金属蛋白进行强大的表征。它结合了含金属活性位点的量子力学(QM)描述和由离散分子动力学(DMD)(QM / DMD)捕获的蛋白质的广泛动力学。 DMD对整个蛋白质进行采样,包括主链和大多数活性位点,金属的直接配位区域除外。 QM作用于具有电子和化学意义的蛋白质,可能包含数十至数百个原子。呼吸量子经典边界在两个机械之间提供了连续的相互反馈。我们使用含铁的电子转运蛋白,rubredoxin及其三个突变体作为模型测试QM / DMD。 QM / DMD可以在合理的时间内为金属蛋白的结构,动力学和电子结构提供可靠的平衡描述。为了说明QM / DMD功能,我们然后预测了儿茶酚O-甲基转移酶Ca 2 + 形式的结构,与天然Mg 2 + 形式,无催化活性。 Mg 2 + 位点是八面体,而Ca 2 + 位点是7坐标,并且具有系统反应部分的错位。骨干调整有助于此更改。 QM / DMD是提供这种级别的结构洞察力的理想之选。

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