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准确的天青蛋白变体还原电位的量子力学/分子力学计算。

Accurate Quantum Mechanical/Molecular Mechanical Calculations of Reduction Potentials in Azurin Variants.

机构信息

Department of Chemistry , Duke University , Durham , North Carolina 27708 , United States.

出版信息

J Chem Theory Comput. 2018 Sep 11;14(9):4948-4957. doi: 10.1021/acs.jctc.8b00403. Epub 2018 Aug 10.

Abstract

Understanding the regulation mechanism and molecular determinants of the reduction potential of metalloprotein is a major challenge. An ab initio quantum mechanical/molecular mechanical (QM/MM) method combining the minimum free energy path (MFEP) and fractional number of electron (FNE) approaches has been developed in our group to simulate the redox processes of large systems. The FNE scheme provides an efficient unique description for the redox process, while the MFEP method provides improved conformational sampling on complex environments such as protein in the QM/MM calculations. The reduction potentials of wild-type and seven mutants of azurin, a type 1 copper metalloprotein, were simulated with the QM/MM-MFEP+FNE approach in this paper. A range of 350 mV for the variations of the reduction potentials of these azurin proteins was reproduced faithfully with relative errors around 20 mV. The correlation between structural interactions and reduction potentials observed in simulations provides in-depth insight into the regulation of reduction potentials, which potentially can also be very useful to the engineering of metalloprotein-based electrocatalysts in artificial photosynthesis. The excellent accuracy and efficiency of the QM/MM-MFEP+FNE approach demonstrate the potential for simulations of many electron transfer processes in condensed phases and biochemical systems.

摘要

理解金属蛋白还原电势的调节机制和分子决定因素是一个主要挑战。我们小组开发了一种从头算量子力学/分子力学(QM/MM)方法,结合最小自由能路径(MFEP)和分数电子数(FNE)方法,用于模拟大体系的氧化还原过程。FNE 方案为氧化还原过程提供了一种有效的独特描述,而 MFEP 方法在 QM/MM 计算中为蛋白质等复杂环境提供了改进的构象采样。本文采用 QM/MM-MFEP+FNE 方法模拟了野生型和七种突变型天青蛋白(一种 1 型铜金属蛋白)的还原电势。这些天青蛋白的还原电势变化范围为 350 mV,相对误差约为 20 mV。模拟中观察到的结构相互作用与还原电势之间的相关性为还原电势的调节提供了深入的见解,这对于基于金属蛋白的人工光合作用电催化剂的工程设计也可能非常有用。QM/MM-MFEP+FNE 方法具有出色的准确性和效率,证明了在凝聚相和生化系统中模拟许多电子转移过程的潜力。

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本文引用的文献

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QM/MM through the 1990s: The First Twenty Years of Method Development and Applications.
Isr J Chem. 2014 Aug;54(8-9):1250-1263. doi: 10.1002/ijch.201400036. Epub 2014 Jul 31.
2
Flexible and Comprehensive Implementation of MD-PMM Approach in a General and Robust Code.
J Chem Theory Comput. 2017 Nov 14;13(11):5506-5514. doi: 10.1021/acs.jctc.7b00341. Epub 2017 Oct 6.
3
Prediction of Reduction Potentials of Copper Proteins with Continuum Electrostatics and Density Functional Theory.
Chemistry. 2017 Nov 2;23(61):15436-15445. doi: 10.1002/chem.201702901. Epub 2017 Sep 21.
4
Theoretical estimation of redox potential of biological quinone cofactors.
J Comput Chem. 2017 Jul 5;38(18):1612-1621. doi: 10.1002/jcc.24802. Epub 2017 May 3.
5
Metal Ion Modeling Using Classical Mechanics.
Chem Rev. 2017 Feb 8;117(3):1564-1686. doi: 10.1021/acs.chemrev.6b00440. Epub 2017 Jan 3.
6
Mechanism of O2 activation and substrate hydroxylation in noncoupled binuclear copper monooxygenases.
Proc Natl Acad Sci U S A. 2016 Oct 25;113(43):12035-12040. doi: 10.1073/pnas.1614807113. Epub 2016 Oct 10.
7
Adiabatic Approximation in Explicit Solvent Models of RedOx Chemistry.
J Chem Theory Comput. 2016 Oct 11;12(10):5111-5116. doi: 10.1021/acs.jctc.6b00746. Epub 2016 Sep 13.
8
Laccase Redox Potentials: pH Dependence and Mutants, a QM/MM Study.
J Phys Chem B. 2016 Sep 8;120(35):9265-76. doi: 10.1021/acs.jpcb.6b04978. Epub 2016 Aug 26.
9
Extending the essential dynamics analysis to investigate molecular properties: application to the redox potential of proteins.
Phys Chem Chem Phys. 2016 Jul 21;18(27):18450-9. doi: 10.1039/c6cp03394f. Epub 2016 Jun 24.

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