School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States.
Department of Physics & Astronomy, California State University, Los Angeles, California 90032, United States.
J Phys Chem B. 2021 Nov 4;125(43):11927-11942. doi: 10.1021/acs.jpcb.1c07547. Epub 2021 Oct 20.
Phosphorylation of select amino acid residues is one of the most common biological mechanisms for regulating protein structures and functions. While computational modeling can be used to explore the detailed structural changes associated with phosphorylation, most molecular mechanics force fields developed for the simulation of phosphoproteins have been noted to be inconsistent with experimental data. In this work, we parameterize force fields for the phosphorylated forms of the amino acids serine, threonine, and tyrosine using the ForceBalance software package with the goal of improving agreement with experiments for these residues. Our optimized force field, denoted as FB18, is parameterized using high-quality ab initio potential energy scans and is designed to be fully compatible with the AMBER-FB15 protein force field. When utilized in MD simulations together with the TIP3P-FB water model, we find that FB18 consistently enhances the prediction of experimental quantities such as NMR couplings and intramolecular hydrogen-bonding propensities in comparison to previously published models. As was reported with AMBER-FB15, we also see improved agreement with the reference QM calculations in regions at and away from local minima. We thus believe that the FB18 parameter set provides a promising route for the further investigation of the varied effects of protein phosphorylation.
磷酸化特定氨基酸残基是调节蛋白质结构和功能的最常见的生物学机制之一。虽然计算建模可用于探索与磷酸化相关的详细结构变化,但大多数为模拟磷酸化蛋白而开发的分子力学力场已被指出与实验数据不一致。在这项工作中,我们使用 ForceBalance 软件包为丝氨酸、苏氨酸和酪氨酸的磷酸化形式参数化力场,目标是提高这些残基与实验的一致性。我们优化的力场,称为 FB18,是使用高质量的从头算势能扫描进行参数化的,旨在与 AMBER-FB15 蛋白质力场完全兼容。当与 TIP3P-FB 水模型一起用于 MD 模拟时,我们发现 FB18 与先前发表的模型相比,一致地提高了实验量(如 NMR 偶合和分子内氢键倾向)的预测能力。与 AMBER-FB15 一样,我们还看到在局部极小值附近和远离局部极小值的区域与参考 QM 计算的一致性得到了改善。因此,我们相信 FB18 参数集为进一步研究蛋白质磷酸化的各种影响提供了一条有希望的途径。