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利用pH适应构象优化蛋白质中的pKa计算。

Optimizing pKa computation in proteins with pH adapted conformations.

作者信息

Kieseritzky Gernot, Knapp Ernst-Walter

机构信息

Fachbereich Biologie, Chemie, Pharmazie/Institute for Chemistry and Biochemistry, Freie Universität Berlin, Takustrasse 6, 14195 Berlin, Germany.

出版信息

Proteins. 2008 May 15;71(3):1335-48. doi: 10.1002/prot.21820.

Abstract

pK(A) in proteins are determined by electrostatic energy computations using a small number of optimized protein conformations derived from crystal structures. In these protein conformations hydrogen positions and geometries of salt bridges on the protein surface were determined self-consistently with the protonation pattern at three pHs (low, ambient, and high). Considering salt bridges at protein surfaces is most relevant, since they open at low and high pH. In the absence of these conformational changes, computed pK(A)(comp) of acidic (basic) groups in salt bridges underestimate (overestimate) experimental pK(A)(exp), dramatically. The pK(A)(comp) for 15 different proteins with 185 known pK(A)(exp) yield an RMSD of 1.12, comparable with two other methods. One of these methods is fully empirical with many adjustable parameters. The other is also based on electrostatic energy computations using many non-optimized side chain conformers but employs larger dielectric constants at short distances of charge pairs that diminish their electrostatic interactions. These empirical corrections that account implicitly for additional conformational flexibility were needed to describe the energetics of salt bridges appropriately. This is not needed in the present approach. The RMSD of the present approach improves if one considers only strongly shifted pK(A)(exp) in contrast to the other methods under these conditions. Our method allows interpreting pK(A)(comp) in terms of pH dependent hydrogen bonding pattern and salt bridge geometries. A web service is provided to perform pK(A) computations.

摘要

蛋白质中的pK(A)是通过静电能计算来确定的,该计算使用了少量从晶体结构中获得的优化蛋白质构象。在这些蛋白质构象中,蛋白质表面氢的位置和盐桥的几何结构与三个pH值(低、环境和高)下的质子化模式自洽确定。考虑蛋白质表面的盐桥最为相关,因为它们在低pH和高pH时会打开。在没有这些构象变化的情况下,盐桥中酸性(碱性)基团的计算pK(A)(comp)会显著低估(高估)实验pK(A)(exp)。对于15种不同的蛋白质(已知185个pK(A)(exp)),计算得到的pK(A)(comp)的均方根偏差(RMSD)为1.12,与其他两种方法相当。其中一种方法完全基于经验且有许多可调参数。另一种方法同样基于静电能计算,使用了许多未优化的侧链构象,但在电荷对距离较短时采用较大的介电常数,以减少它们之间的静电相互作用。这些隐含考虑了额外构象灵活性的经验校正对于恰当地描述盐桥的能量学是必要的。在本方法中则不需要。与这些条件下的其他方法相比,如果只考虑强烈偏移的pK(A)(exp),本方法的RMSD会有所改善。我们的方法允许根据pH依赖的氢键模式和盐桥几何结构来解释pK(A)(comp)。还提供了一个网络服务来进行pK(A)计算。

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