Riccardi Demian, Schaefer Patricia, Cui Qiang
Department of Chemistry and Theoretical Chemistry Institute, University of Wisconsin, Madison, 1101 University Avenue, Madison, Wisconsin 53706, USA.
J Phys Chem B. 2005 Sep 22;109(37):17715-33. doi: 10.1021/jp0517192.
The accuracy of biological simulations depends, in large part, on the treatment of electrostatics. Due to the availability of accurate experimental values, calculation of pKa provides stringent evaluation of computational methods. The generalized solvent boundary potential (GSBP) and Ewald summation electrostatic treatments were recently implemented for combined quantum mechanical and molecular mechanics (QM/MM) simulations by our group. These approaches were tested by calculating pKa shifts due to differences in electronic structure and electrostatic environment; the shifts were determined for a series of small molecules in solution, using various electrostatic treatments, and two residues (His 31, Lys 102) in the M102K T4-lysozyme mutant with large pKa shifts, using the GSBP approach. The calculations utilized a free energy perturbation scheme with the QM/MM potential function involving the self-consistent charge density functional tight binding (SCC-DFTB) and CHARMM as the QM and MM methods, respectively. The study of small molecules demonstrated that inconsistent electrostatic models produced results that were difficult to correct in a robust manner; by contrast, extended electrostatics, GSBP, and Ewald simulations produced consistent results once a bulk solvation contribution was carefully chosen. In addition to the electrostatic treatment, the pKa shifts were also sensitive to the level of the QM method and the scheme of treating QM/MM Coulombic interactions; however, simple perturbative corrections based on SCC-DFTB/CHARMM trajectories and higher level single point energy calculations were found to give satisfactory results. Combining all factors gave a root-mean-square difference of 0.7 pKa units for the relative pKa values of the small molecules compared to experiment. For the residues in the lysozyme, an accurate pKa shift was obtained for His 31 with multiple nanosecond simulations. For Lys 102, however, the pKa shift was estimated to be too large, even after more than 10 nanosecond simulations for each lambda window; the difficulty was due to the significant, but slow, reorganization of the protein and water structure when Lys 102 was protonated. The simulations support that Lys 102 is deprotonated in the X-ray structure and the protein is highly destabilized when this residue is protonated.
生物模拟的准确性在很大程度上取决于静电作用的处理。由于有准确的实验值,pKa 的计算为计算方法提供了严格的评估。我们小组最近在组合量子力学和分子力学(QM/MM)模拟中采用了广义溶剂边界势(GSBP)和埃瓦尔德求和静电处理方法。通过计算由于电子结构和静电环境差异导致的 pKa 位移来测试这些方法;使用各种静电处理方法确定了溶液中一系列小分子的位移,并使用 GSBP 方法确定了 M102K T4-溶菌酶突变体中两个具有大 pKa 位移的残基(His 31、Lys 102)的位移。计算采用了自由能微扰方案,其 QM/MM 势函数分别涉及自洽电荷密度泛函紧束缚(SCC-DFTB)和 CHARMM 作为 QM 和 MM 方法。对小分子的研究表明,不一致的静电模型产生的结果难以以稳健的方式校正;相比之下,一旦仔细选择了本体溶剂化贡献,扩展静电、GSBP 和埃瓦尔德模拟会产生一致的结果。除了静电处理外,pKa 位移还对 QM 方法的水平和处理 QM/MM 库仑相互作用的方案敏感;然而,发现基于 SCC-DFTB/CHARMM 轨迹的简单微扰校正和更高水平的单点能量计算能给出令人满意的结果。综合所有因素,小分子相对 pKa 值与实验相比的均方根差为 0.7 个 pKa 单位。对于溶菌酶中的残基,通过多次纳秒模拟获得了 His 31 的准确 pKa 位移。然而,对于 Lys 102,即使在每个 λ 窗口进行了超过 10 纳秒的模拟后,估计其 pKa 位移仍然过大;困难在于当 Lys 102 质子化时蛋白质和水结构的显著但缓慢的重组。模拟结果支持 Lys 102 在 X 射线结构中是去质子化的,并且当该残基质子化时蛋白质会高度不稳定。