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Quantum mechanics and mixed quantum mechanics/molecular mechanics simulations of model nerve agents with acetylcholinesterase

机译:用乙酰胆碱酯酶模拟神经毒剂的量子力学和混合量子力学/分子力学模拟

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The accurate modeling of biological processes presents major computational difficulties owing to the inherent complexity of the macromolecular systems of interest. Simulations of biochemical reactivity tend to require highly computationally intensive quantum mechanical methods, but localized chemical effects tend to depend significantly on properties of the extended biological environment - a regime far more readily examined with lower-level classical empirical models. Mixed quantum/classical techniques are gaining in popularity as a means of bridging these competing requirements. Here we present results comparing two quantum mechanics/molecular mechanics implementations (the SIMOMM technique of Gordon et al. as implemented in GAMESS, and the ONIOM technique of Morokuma et al. found in Gaussian 98) as performed on the enzyme acetylcholinesterase and model nerve agents. This work represents part of the initial phase of a DoD HPCMP Challenge project in which we are attempting to reliably characterize the biochemical processes responsible for nerve agent activity and inhibition, thereby allowing predictions on compounds unrelated to those already studied. [References: 27]
机译:由于感兴趣的大分子系统固有的复杂性,生物过程的精确建模带来了主要的计算困难。生化反应性的模拟往往需要高度计算量的量子力学方法,但是局部化学作用往往会很大程度上取决于扩展的生物环境的性质-这种机制更容易用较低水平的经典经验模型进行检验。作为弥合这些竞争需求的一种手段,混合量子/经典技术越来越流行。在这里,我们将比较两种量子力学/分子力学实现(在GAMESS中实现的Gordon等人的SIMOMM技术和在高斯98中发现的Morokuma等人的ONIOM技术)对乙酰胆碱酯酶和模型神经毒剂进行比较的结果。 。这项工作代表了国防部HPCMP挑战项目初始阶段的一部分,在该项目中,我们试图可靠地表征负责神经毒剂活性和抑制作用的生化过程,从而允许对与已经研究的化合物无关的化合物进行预测。 [参考:27]

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