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一种自洽的、微环境调制的屏蔽库仑势近似方法,用于计算蛋白质中pH依赖的静电效应。

A self-consistent, microenvironment modulated screened coulomb potential approximation to calculate pH-dependent electrostatic effects in proteins.

作者信息

Mehler E L, Guarnieri F

机构信息

Department of Physiology and Biophysics, Mount Sinai School of Medicine, CUNY, New York, New York 10029, USA.

出版信息

Biophys J. 1999 Jul;77(1):3-22. doi: 10.1016/S0006-3495(99)76868-2.

Abstract

An improved approach is presented for calculating pH-dependent electrostatic effects in proteins using sigmoidally screened Coulomb potentials (SCP). It is hypothesized that a key determinant of seemingly aberrant behavior in pKa shifts is due to the properties of the unique microenvironment around each residue. To help demonstrate this proposal, an approach is developed to characterize the microenvironments using the local hydrophobicity/hydrophilicity around each residue of the protein. The quantitative characterization of the microenvironments shows that the protein is a complex mosaic of differing dielectric regions that provides a physical basis for modifying the dielectric screening functions: in more hydrophobic microenvironments the screening decreases whereas the converse applies to more hydrophilic regions. The approach was applied to seven proteins providing more than 100 measured pKa values and yielded a root mean square deviation of 0.5 between calculated and experimental values. The incorporation of the local hydrophobicity characteristics into the algorithm allowed the resolution of some of the more intractable problems in the calculation of pKa. Thus, the divergent shifts of the pKa of Glu-35 and Asp-66 in hen egg white lysozyme, which are both about 90% buried, was correctly predicted. Mechanistically, the divergence occurs because Glu-35 is in a hydrophobic microenvironment, while Asp-66 is in a hydrophilic microenvironment. Furthermore, because the calculation of the microenvironmental effects takes very little CPU time, the computational speed of the SCP formulation is conserved. Finally, results from different crystal structures of a given protein were compared, and it is shown that the reliability of the calculated pKa values is sufficient to allow identification of conformations that may be more relevant for the solution structure.

摘要

本文提出了一种改进方法,用于使用S形屏蔽库仑势(SCP)计算蛋白质中pH依赖的静电效应。据推测,pKa位移中看似异常行为的一个关键决定因素是每个残基周围独特微环境的性质。为了帮助证明这一观点,开发了一种方法,利用蛋白质每个残基周围的局部疏水性/亲水性来表征微环境。微环境的定量表征表明,蛋白质是由不同介电区域组成的复杂镶嵌体,这为修改介电屏蔽函数提供了物理基础:在疏水性更强的微环境中屏蔽作用减弱,而在亲水性更强的区域则相反。该方法应用于七种蛋白质,提供了100多个测量的pKa值,计算值与实验值之间的均方根偏差为0.5。将局部疏水性特征纳入算法,使得在计算pKa时能够解决一些更棘手的问题。因此,正确预测了鸡蛋清溶菌酶中Glu-35和Asp-66的pKa的不同位移,它们都被埋藏了约90%。从机制上讲,这种差异的出现是因为Glu-35处于疏水性微环境中,而Asp-66处于亲水性微环境中。此外,由于微环境效应的计算只需要很少的CPU时间,因此SCP公式的计算速度得以保留。最后,比较了给定蛋白质不同晶体结构的结果,结果表明,计算得到的pKa值的可靠性足以识别可能与溶液结构更相关的构象。

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本文引用的文献

1
Electrostatic contributions to the binding of Ca2+ in calbindin mutants. A Monte Carlo study.
Biophys Chem. 1990 Oct;38(1-2):179-83. doi: 10.1016/0301-4622(90)80053-a.
2
The effect of protein relaxation on charge-charge interactions and dielectric constants of proteins.
Biophys J. 1998 Apr;74(4):1744-53. doi: 10.1016/S0006-3495(98)77885-3.
4
Incorporating protein conformational flexibility into the calculation of pH-dependent protein properties.
Biophys J. 1997 May;72(5):2075-93. doi: 10.1016/S0006-3495(97)78851-9.
6
Measurement and modelling of sequence-specific pKa values of lysine residues in calbindin D9k.
J Mol Biol. 1996 Jun 21;259(4):828-39. doi: 10.1006/jmbi.1996.0361.
7
The determinants of pKas in proteins.
Biochemistry. 1996 Jun 18;35(24):7819-33. doi: 10.1021/bi9601565.

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