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使用密度泛函理论对双核非血红素铁酶的核共振振动光谱数据进行建模。

Modeling nuclear resonance vibrational spectroscopic data of binuclear non-heme iron enzymes using density functional theory.

作者信息

Park Kiyoung, Solomon Edward I

机构信息

Department of Chemistry, Stanford University, 333 Campus Drive, Stanford, CA 94305, USA.

出版信息

Can J Chem. 2014 Oct;92(10):975-978. doi: 10.1139/cjc-2014-0067. Epub 2014 Apr 15.

Abstract

Nuclear resonance vibrational spectroscopy (NRVS) is a powerful technique that can provide geometric structural information on key reaction intermediates of Fe-containing systems when utilized in combination with density functional theory (DFT). However, in the case of binuclear non-heme iron enzymes, DFT-predicted NRVS spectra have been found to be sensitive to truncation method used to model the active sites of the enzymes. Therefore, in this study various-level truncation schemes have been tested to predict the NRVS spectrum of a binuclear non-heme iron enzyme, and a reasonably sized DFT model that is suitable for employing the NRVS/DFT combined methodology to characterize binuclear non-heme iron enzymes has been developed.

摘要

核共振振动光谱(NRVS)是一种强大的技术,当与密度泛函理论(DFT)结合使用时,它可以提供含铁体系关键反应中间体的几何结构信息。然而,对于双核非血红素铁酶,已发现DFT预测的NRVS光谱对用于模拟酶活性位点的截断方法敏感。因此,在本研究中,测试了各种水平的截断方案以预测双核非血红素铁酶的NRVS光谱,并开发了一个尺寸合适的DFT模型,该模型适用于采用NRVS/DFT组合方法来表征双核非血红素铁酶。

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