Privat Cristian, Madurga Sergio, Mas Francesc, Rubio-Martínez Jaime
Department of Material Science and Physical Chemistry & Research Institute of Theoretical and Computational Chemistry (IQTCUB), University of Barcelona, C/Martí i Franquès 1, 08028 Barcelona, Spain.
Polymers (Basel). 2020 Dec 29;13(1):99. doi: 10.3390/polym13010099.
Solvent pH is an important property that defines the protonation state of the amino acids and, therefore, modulates the interactions and the conformational space of the biochemical systems. Generally, this thermodynamic variable is poorly considered in Molecular Dynamics (MD) simulations. Fortunately, this lack has been overcome by means of the Constant pH Molecular Dynamics (CPHMD) methods in the recent decades. Several studies have reported promising results from these approaches that include pH in simulations but focus on the prediction of the effective pKa of the amino acids. In this work, we want to shed some light on the CPHMD method and its implementation in the AMBER suitcase from a conformational point of view. To achieve this goal, we performed CPHMD and conventional MD (CMD) simulations of six protonatable amino acids in a blocked tripeptide structure to compare the conformational sampling and energy distributions of both methods. The results reveal strengths and weaknesses of the CPHMD method in the implementation of AMBER18 version. The change of the protonation state according to the chemical environment is presumably an improvement in the accuracy of the simulations. However, the simulations of the deprotonated forms are not consistent, which is related to an inaccurate assignment of the partial charges of the backbone atoms in the CPHMD residues. Therefore, we recommend the CPHMD methods of AMBER program but pointing out the need to compare structural properties with experimental data to bring reliability to the conformational sampling of the simulations.
溶剂pH是一个重要性质,它决定了氨基酸的质子化状态,进而调节生化系统的相互作用和构象空间。一般来说,这种热力学变量在分子动力学(MD)模拟中很少被考虑。幸运的是,近几十年来通过恒定pH分子动力学(CPHMD)方法克服了这一不足。几项研究报告了这些方法取得的有前景的结果,这些方法在模拟中纳入了pH,但侧重于预测氨基酸的有效pKa。在这项工作中,我们想从构象的角度阐明CPHMD方法及其在AMBER软件包中的实现。为实现这一目标,我们对一个封闭三肽结构中的六种可质子化氨基酸进行了CPHMD和传统MD(CMD)模拟,以比较两种方法的构象采样和能量分布。结果揭示了CPHMD方法在AMBER18版本实现中的优缺点。根据化学环境的质子化状态变化可能提高了模拟的准确性。然而,去质子化形式的模拟并不一致,这与CPHMD残基中主链原子部分电荷的不准确分配有关。因此,我们推荐AMBER程序的CPHMD方法,但指出需要将结构性质与实验数据进行比较,以使模拟的构象采样具有可靠性。