Huang Wei, Ravikumar Krishnakumar M, Chance Mark R, Yang Sichun
Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio.
Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, Ohio; Department of Pharmacology, Case Western Reserve University, Cleveland, Ohio.
Biophys J. 2015 Jan 6;108(1):107-15. doi: 10.1016/j.bpj.2014.11.013.
Measurements from hydroxyl radical footprinting (HRF) provide rich information about the solvent accessibility of amino acid side chains of a protein. Traditional HRF data analyses focus on comparing the difference in the modification/footprinting rate of a specific site to infer structural changes across two protein states, e.g., between a free and ligand-bound state. However, the rate information itself is not fully used for the purpose of comparing different protein sites within a protein on an absolute scale. To provide such a cross-site comparison, we present a new, to our knowledge, data analysis algorithm to convert the measured footprinting rate constant to a protection factor (PF) by taking into account the known intrinsic reactivity of amino acid side chain. To examine the extent to which PFs can be used for structural interpretation, this PF analysis is applied to three model systems where radiolytic footprinting data are reported in the literature. By visualizing structures colored with the PF values for individual peptides, a rational view of the structural features of various protein sites regarding their solvent accessibility is revealed, where high-PF regions are buried and low-PF regions are more exposed to the solvent. Furthermore, a detailed analysis correlating solvent accessibility and local structural contacts for gelsolin shows a statistically significant agreement between PF values and various structure measures, demonstrating that the PFs derived from this PF analysis readily explain fundamental HRF rate measurements. We also tested this PF analysis on alternative, chemical-based HRF data, showing improved correlations of structural properties of a model protein barstar compared to examining HRF rate data alone. Together, this PF analysis not only permits a novel, to our knowledge, approach of mapping protein structures by using footprinting data, but also elevates the use of HRF measurements from a qualitative, cross-state comparison to a quantitative, cross-site assessment of protein structures in the context of individual conformational states of interest.
羟基自由基足迹法（HRF）的测量提供了有关蛋白质氨基酸侧链溶剂可及性的丰富信息。传统的HRF数据分析侧重于比较特定位点修饰/足迹形成速率的差异，以推断两种蛋白质状态之间的结构变化，例如在游离状态和配体结合状态之间。然而，速率信息本身并未完全用于在绝对尺度上比较蛋白质内不同蛋白质位点的目的。为了进行这种跨位点比较，据我们所知，我们提出了一种新的数据分析算法，通过考虑氨基酸侧链已知的内在反应性，将测得的足迹形成速率常数转换为保护因子（PF）。为了检验PF可用于结构解释的程度，将这种PF分析应用于文献中报道了辐射分解足迹数据的三个模型系统。通过可视化用各个肽段的PF值着色的结构，揭示了各种蛋白质位点关于其溶剂可及性的结构特征的合理视图，其中高PF区域被掩埋，低PF区域更暴露于溶剂中。此外，对凝溶胶蛋白的溶剂可及性和局部结构接触进行的详细分析表明，PF值与各种结构测量之间存在统计学上的显著一致性，这表明从这种PF分析得出的PF很容易解释基本的HRF速率测量结果。我们还在基于化学的替代性HRF数据上测试了这种PF分析，结果表明，与仅检查HRF速率数据相比，模型蛋白巴氏杆菌素的结构特性的相关性有所改善。总之，这种PF分析不仅允许我们采用一种据我们所知新颖的方法，即利用足迹数据绘制蛋白质结构，而且还将HRF测量的用途从定性的跨状态比较提升到在感兴趣的单个构象状态背景下对蛋白质结构进行定量的跨位点评估。
