Goh Garrett B, Hulbert Benjamin S, Zhou Huiqing, Brooks Charles L
Department of Chemistry, University of Michigan, Ann Arbor, Michigan, 48109.
Proteins. 2014 Jul;82(7):1319-31. doi: 10.1002/prot.24499. Epub 2014 Jan 15.
pH is a ubiquitous regulator of biological activity, including protein-folding, protein-protein interactions, and enzymatic activity. Existing constant pH molecular dynamics (CPHMD) models that were developed to address questions related to the pH-dependent properties of proteins are largely based on implicit solvent models. However, implicit solvent models are known to underestimate the desolvation energy of buried charged residues, increasing the error associated with predictions that involve internal ionizable residue that are important in processes like hydrogen transport and electron transfer. Furthermore, discrete water and ions cannot be modeled in implicit solvent, which are important in systems like membrane proteins and ion channels. We report on an explicit solvent constant pH molecular dynamics framework based on multi-site λ-dynamics (CPHMD(MSλD)). In the CPHMD(MSλD) framework, we performed seamless alchemical transitions between protonation and tautomeric states using multi-site λ-dynamics, and designed novel biasing potentials to ensure that the physical end-states are predominantly sampled. We show that explicit solvent CPHMD(MSλD) simulations model realistic pH-dependent properties of proteins such as the Hen-Egg White Lysozyme (HEWL), binding domain of 2-oxoglutarate dehydrogenase (BBL) and N-terminal domain of ribosomal protein L9 (NTL9), and the pKa predictions are in excellent agreement with experimental values, with a RMSE ranging from 0.72 to 0.84 pKa units. With the recent development of the explicit solvent CPHMD(MSλD) framework for nucleic acids, accurate modeling of pH-dependent properties of both major class of biomolecules-proteins and nucleic acids is now possible.
pH是生物活性的普遍调节剂,包括蛋白质折叠、蛋白质-蛋白质相互作用和酶活性。现有的用于解决与蛋白质pH依赖性特性相关问题的恒定pH分子动力学(CPHMD)模型主要基于隐式溶剂模型。然而,已知隐式溶剂模型会低估埋藏带电残基的去溶剂化能量,增加与涉及内部可电离残基的预测相关的误差,这些残基在氢传输和电子转移等过程中很重要。此外,在隐式溶剂中无法对离散的水和离子进行建模,而这在膜蛋白和离子通道等系统中很重要。我们报道了一种基于多位点λ动力学的显式溶剂恒定pH分子动力学框架(CPHMD(MSλD))。在CPHMD(MSλD)框架中,我们使用多位点λ动力学在质子化和互变异构状态之间进行无缝炼金术转变,并设计了新颖的偏置势以确保主要采样物理终态。我们表明,显式溶剂CPHMD(MSλD)模拟能够模拟蛋白质如鸡蛋清溶菌酶(HEWL)、2-氧代戊二酸脱氢酶结合结构域(BBL)和核糖体蛋白L9 N端结构域(NTL9)的实际pH依赖性特性,并且pKa预测与实验值高度吻合,均方根误差范围为0.72至0.84 pKa单位。随着用于核酸的显式溶剂CPHMD(MSλD)框架的最新发展,现在有可能对蛋白质和核酸这两类主要生物分子的pH依赖性特性进行精确建模。