Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States.
J Phys Chem B. 2022 Oct 13;126(40):7806-7817. doi: 10.1021/acs.jpcb.2c03642. Epub 2022 Oct 4.
Precisely quantifying the magnitude, direction, and biological functions of electric fields in proteins has long been an outstanding challenge in the field. The most widely implemented experimental method to measure such electric fields at a particular residue in a protein has been through changes in p of titratable residues. While many computational strategies exist to predict these values, it has been difficult to do this accurately or connect predicted results to key structural or mechanistic features of the molecule. Here, we used experimentally determined p values of the fluorophore in superfolder green fluorescent protein (GFP) with amino acid mutations made at position Thr 203 to evaluate the p prediction ability of molecular dynamics (MD) simulations using a polarizable force field, AMOEBA. Structure ensembles from AMOEBA were used to calculate p values of the GFP fluorophore. The calculated p values were then compared to trajectories using a conventional fixed charge force field (Amber03 ff). We found that the position of water molecules included in the p calculation had opposite effects on the p values between the trajectories from AMOEBA and Amber03 force fields. In AMOEBA trajectories, the inclusion of water molecules within 35 Å of the fluorophore decreased the difference between the predicted and experimental values, resulting in calculated p values that were within an average of 0.8 p unit from the experimental results. On the other hand, in Amber03 trajectories, including water molecules that were more than 5 Å from the fluorophore increased the differences between the calculated and experimental p values. The inaccuracy of p predictions determined from Amber03 trajectories was caused by a significant stabilization of the deprotonated chromophore's free energy compared to the result in AMOEBA. We rationalize the cutoffs for explicit water molecules when calculating p to better predict the electrostatic environment surrounding the fluorophore buried in GFP. We discuss how the results from this work will assist the prospective prediction of p values or other electrostatic effects in a wide variety of folded proteins.
精确量化蛋白质中电场的大小、方向和生物学功能一直是该领域的一个突出挑战。测量蛋白质中特定残基处这种电场的最广泛应用的实验方法是通过可滴定残基的 p 值变化。虽然存在许多预测这些值的计算策略，但很难准确地做到这一点，或者将预测结果与分子的关键结构或机制特征联系起来。在这里，我们使用实验确定的超折叠绿色荧光蛋白 (GFP) 中的荧光团的 p 值，以及在位置 Thr 203 处进行的氨基酸突变，来评估使用极化力场 AMOEBA 的分子动力学 (MD) 模拟的 p 值预测能力。使用 AMOEBA 的结构集合来计算 GFP 荧光团的 p 值。然后将计算出的 p 值与使用传统固定电荷力场 (Amber03 ff) 的轨迹进行比较。我们发现，p 值计算中包含的水分子的位置对 AMOEBA 和 Amber03 力场轨迹的 p 值有相反的影响。在 AMOEBA 轨迹中，在荧光团 35 Å 范围内包含水分子会减小预测值与实验值之间的差异，从而导致计算出的 p 值与实验结果的平均差异在 0.8 p 单位内。另一方面，在 Amber03 轨迹中，包含距离荧光团超过 5 Å 的水分子会增加计算值与实验 p 值之间的差异。Amber03 轨迹中 p 值预测的不准确性是由于与 AMOEBA 的结果相比，去质子化生色团的自由能显著稳定化所致。我们合理化了在计算 p 值时包含显式水分子的截止值，以更好地预测埋藏在 GFP 中的荧光团周围的静电环境。我们讨论了这项工作的结果将如何协助广泛折叠蛋白质中 p 值或其他静电效应的预测。
