Estimation of Hydrogen-Exchange Protection Factors from MD Simulation Based on Amide Hydrogen Bonding Analysis

Hydrogen
exchange (HX) studies have provided critical insight into our understanding
of protein folding, structure, and dynamics. More recently, hydrogen
exchange mass spectrometry (HX-MS) has become a widely applicable
tool for HX studies. The interpretation of the wealth of data generated
by HX-MS experiments as well as other HX methods would greatly benefit
from the availability of exchange predictions derived from structures
or models for comparison with experiment. Most reported computational
HX modeling studies have employed solvent-accessible-surface-area
based metrics in attempts to interpret HX data on the basis of structures
or models. In this study, a computational HX-MS prediction method
based on classification of the amide hydrogen bonding modes mimicking
the local unfolding model is demonstrated. Analysis of the NH bonding
configurations from molecular dynamics (MD) simulation snapshots is
used to determine partitioning over bonded and nonbonded NH states
and is directly mapped into a protection factor (PF) using a logistics
growth function. Predicted PFs are then used for calculating deuteration
values of peptides and compared with experimental data. Hydrogen exchange
MS data for fatty acid synthase thioesterase (FAS-TE) collected for
a range of pHs and temperatures was used for detailed evaluation of
the approach. High correlation between prediction and experiment for
observable fragment peptides is observed in the FAS-TE and additional
benchmarking systems that included various apo/holo proteins for which
literature data were available. In addition, it is shown that HX modeling
can improve experimental resolution through decomposition of in-exchange
curves into rate classes, which correlate with prediction from MD.
Successful rate class decompositions provide further evidence that
the presented approach captures the underlying physical processes
correctly at the single residue level. This assessment is further
strengthened in a comparison of residue resolved protection factor
predictions for staphylococcal nuclease with NMR data, which was also
used to compare prediction performance with other algorithms described
in the literature. The demonstrated transferable and scalable MD based
HX prediction approach adds significantly to the available tools for
HX-MS data interpretation based on available structures and models.

氢交换（HX）研究为我们对蛋白质折叠、结构和动态变化的理解提供了关键性的洞见。近年来，氢交换质谱法（HX-MS）已成为氢交换研究中的一个广泛应用工具。对由HX-MS实验以及其他HX方法产生的丰富数据的解读，若能辅以从结构或模型中推导出的交换预测结果进行比较，将极大提高其准确性和有效性。大多数已报道的计算氢交换建模研究都采用了溶剂可及表面积（solvent-accessible-surface-area）为基础的指标，试图基于结构或模型对氢交换数据进行分析。在本研究中，我们展示了一种基于酰胺氢键模式分类的氢交换质谱法预测方法，该方法模拟了局部展开模型。通过分析分子动力学（MD）模拟快照中的NH键合配置，我们确定了键合NH和非键合NH状态之间的分配，并利用逻辑增长函数将其直接映射到保护因子（PF）。预测的PF随后被用于计算肽段的氘代值，并与实验数据进行了比较。针对脂肪酸合成酶硫酯酶（FAS-TE）在不同pH值和温度下收集的氢交换质谱数据，我们对该方法进行了详细的评估。在FAS-TE以及其他包含多种无活性/活性蛋白的基准测试系统中，观察到预测结果与实验数据在可观察的片段肽之间具有较高的相关性。此外，研究表明，通过将交换曲线分解为速率类别，可以分解实验分辨率，这些速率类别与MD预测相关。成功的速率类别分解进一步证实了所提出的方法在单个残基水平上正确捕捉了潜在物理过程。这一评估通过比较从NMR数据中解析出的残基分辨保护因子预测与文献中描述的其他算法的性能预测，得到了进一步的加强。所展示的基于MD的氢交换预测方法，具有可迁移性和可扩展性，为基于现有结构和模型对HX-MS数据进行解释的可供选择工具增加了新的重要功能。