Fast empirical pKa prediction by Ewald summation

被引:360
作者
Krieger, Elmar
Nielsen, Jens E.
Spronk, Chris A. E. M.
Vriend, Gert
机构
[1] Radboud Univ Nijmegen, Ctr Mol & Biomol Informat, NL-6525 ED Nijmegen, Netherlands
[2] Univ Coll Dublin, UCD Conway Inst, Ctr Synth & Chem Biol, Sch Biomol & Biomed Sci, Dublin 4, Ireland
关键词
protein pK(a) prediction; Poisson-Boltzmann; particle mesh Ewald; crystal space; force field optimization;
D O I
10.1016/j.jmgm.2006.02.009
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
pK(a) calculations for macromolecules are normally performed by solving the Poisson-Boltzmann equation, accounting for the different dielectric constants of solvent and solute, as well as the ionic strength. Despite the large number of successful applications, there are some situations where the current algorithms are not suitable: (1) large scale, high-throughput analysis which requires calculations to be completed within a fraction of a second, e.g. when permanently monitoring pK(a) shifts during a molecular dynamics simulation; (2) prediction of pK(a)s in periodic boundaries, e.g. when reconstructing entire protein crystal unit cells from PDB; files, including the correct protonation patterns at experimental pH. Such in silico crystals are needed by 'self-parameterizing' molecular dynamics force fields like YASARA YAMBER, that optimize their parameters while energy-minimizing high-resolution protein crystals. To address both problems, we define an empirical equation that expresses the pK(a) as a function of electrostatic potential, hydrogen bonds and accessible surface area. The electrostatic potential is evaluated by Ewald summation, which captures periodic crystal environments and the uncertainty in atom positions using Gaussian charge densities. The empirical proportionality constants are derived from 217 experimentally determined pK(a)s, and despite its simplicity, this pK(a) calculation method reaches a high overall jack-knifed accuracy, and is fast enough to be used during a molecular dynamics simulation. A reliable null-model to judge pK(a) prediction accuracies is also presented. (c) 2006 Elsevier Inc. All rights reserved.
引用
收藏
页码:481 / 486
页数:6
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