Hydrogen Donor-Acceptor Fluctuations from Kinetic Isotope Effects: A Phenomenological Model

被引:51
作者
Roston, Daniel [1 ]
Cheatum, Christopher M. [1 ]
Kohen, Amnon [1 ]
机构
[1] Univ Iowa, Dept Chem, Iowa City, IA 52242 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
PROTON-TRANSFER REACTIONS; HYDRIDE TRANSFER; TEMPERATURE-DEPENDENCE; ENZYME DYNAMICS; ALCOHOL-DEHYDROGENASE; SOYBEAN LIPOXYGENASE; THEORETICAL-ANALYSIS; NONADIABATIC PROTON; BARRIER COMPRESSION; ELECTRON-TRANSFER;
D O I
10.1021/bi300613e
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Kinetic isotope effects (KIEs) and their temperature dependence can probe the structural and dynamic nature of enzyme-catalyzed proton or hydride transfers. The molecular interpretation of their temperature dependence requires expensive and specialized quantum mechanics/molecular mechanics (QM/MM) Calculations to provide a quantitative molecular understanding. Currently available phenomenological models use a nonadiabatic assumption that is not appropriate for most hydride and proton-transfer reactions, while others require more parameters than the experimental data justify. Here We propose a phenomenological interpretation of KIEs based on a simple method to quantitatively link the size and temperature dependence of KIEs to a conformational distribution of the catalyzed reaction. This model assumes adiabatic hydrogen tunneling, and by fitting experimental KIE data, the model yields a population distribution for fluctuations of the distance between donor and acceptor atoms. Fits to data from a variety of proton and hydride transfers catalyzed by enzymes and their mutants, as well as nonenzymatic reactions, reveal that steeply temperature-dependent KIEs indicate the presence of at least two distinct conformational populations, each with different kinetic behaviors. We present the results of these. calculations for several published cases and discuss how the predictions of the calculations might be experimentally tested. This analysis does not replace molecular QM/MM investigations, but it provides a fast and accessible way to quantitatively interpret KIEs in the context of a Marcus-like model.
引用
收藏
页码:6860 / 6870
页数:11
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