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蛋白质pH依赖性性质的预测。

Prediction of pH-dependent properties of proteins.

作者信息

Antosiewicz J, McCammon J A, Gilson M K

机构信息

Department of Chemistry, University of Houston, TX 77204-5641.

出版信息

J Mol Biol. 1994 May 6;238(3):415-36. doi: 10.1006/jmbi.1994.1301.

Abstract

We describe what may be the most accurate approach currently available for the calculation of the pKas of ionizable groups in proteins. The accuracy is assessed by comparison of computed pKas with 60 measured pKas in a total of seven proteins. The overall root-mean-square error is 0.89 pKa units. Linear regression analysis of computed versus measured pKas yields a slope of 0.95, y-intercept of -0.02 and a correlation coefficient of 0.96. The proposed approach also picks out many of the shifted pKas of groups in enzyme active sites and special salt bridges. However, it does yield several over-shifted pKas and tends to underestimate pKa shifts which result from desolvation effects. We examine the ability of the new approach to reproduce the dependence of protein stability upon pH, using the ionization polynomial formalism. Overall features of the stability curves are reproduced, but the quantitative agreement is not particularly good. The reasons for the disagreement may have to do both with insufficient accuracy in the theory and with uncertainty in the nature of the unfolded state of proteins. The methodology described here is based upon finite difference solutions of the Poisson-Boltzmann equation. Its success depends upon the use of the rather high protein dielectric constant of 20. However, theoretical considerations and the fact that pKa shifts which result from desolvation are underestimated here imply that the dielectric constant of the protein interior actually is lower than 20. We suggest that the high protein dielectric constant improves the overall agreement with experiment because it accounts approximately for phenomena which tend to mitigate pKa shifts and which are not specifically included in the model. These include conformational relaxation and specific ion-binding. Future models based upon a low protein dielectric constant and treating such phenomena explicitly might yield improved agreement with experiment.

摘要

我们描述了一种目前可能是计算蛋白质中可电离基团pKa最准确的方法。通过将计算得到的pKa与总共七种蛋白质中60个测量得到的pKa进行比较来评估其准确性。总体均方根误差为0.89个pKa单位。计算得到的pKa与测量得到的pKa的线性回归分析得出斜率为0.95,y轴截距为 -0.02,相关系数为0.96。所提出的方法还能识别出酶活性位点和特殊盐桥中许多基团的pKa位移。然而,它确实产生了一些位移过大的pKa,并且往往低估了由去溶剂化效应导致的pKa位移。我们使用电离多项式形式来研究这种新方法重现蛋白质稳定性对pH依赖性的能力。稳定性曲线的总体特征得以重现,但定量一致性并不是特别好。不一致的原因可能既与理论的准确性不足有关,也与蛋白质未折叠状态的性质存在不确定性有关。这里描述的方法基于泊松 - 玻尔兹曼方程的有限差分法。其成功依赖于使用相当高的蛋白质介电常数20。然而,理论考量以及此处去溶剂化导致的pKa位移被低估这一事实意味着蛋白质内部的介电常数实际上低于20。我们认为高蛋白质介电常数改善了与实验的总体一致性,因为它大致考虑了一些往往会减轻pKa位移且未在模型中具体包含的现象。这些现象包括构象弛豫和特定离子结合。基于低蛋白质介电常数并明确处理此类现象的未来模型可能会与实验达成更好的一致性。

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