\(^1\)H ENDOR spectra of tyrosyl radicals (Y\(^\bullet\)) have been the subject of numerous EPR spectroscopic studies due to their importance in biology. Nevertheless, assignment of all internal \(^1\)H hyperfine couplings has been challenging because of substantial spectral overlap. Recently, using 263 GHz ENDOR in conjunction with statistical analysis, we could identify the signature of the H\(^{\upbeta _2}\) coupling in the essential Y\(_{122}\) radical of Escherichia coli ribonucleotide reductase, and modeled it with a distribution of radical conformations. Here, we demonstrate that this analysis can be extended to the full-width \(^1\)H ENDOR spectra that contain the larger H\(^{\upbeta _1}\) coupling. The H\(^{\upbeta _2}\) and H\(^{\upbeta _1}\) couplings are related to each other through the ring dihedral and report on the amino acid conformation. The 263 GHz ENDOR data, acquired in batches instead of averaging, and data processing by a new “drift model” allow reconstructing the ENDOR spectra with statistically meaningful confidence intervals and separating them from baseline distortions. Spectral simulations using a distribution of ring dihedral angles confirm the presence of a conformational distribution, consistent with the previous analysis of the H\(^{\upbeta _2}\) coupling. The analysis was corroborated by 94 GHz \(^2\)H ENDOR of deuterated Y\(_{122}^\bullet\). These studies provide a starting point to investigate low populated states of tyrosyl radicals in greater detail.

\(^1\)酪氨酰自由基 (Y \(^\bullet\) ) 的H ENDOR 光谱因其在生物学中的重要性而成为众多 EPR 光谱研究的主题。然而，由于大量的光谱重叠，所有内部\(^1\) H 超精细耦合的分配一直具有挑战性。最近，使用 263 GHz ENDOR 结合统计分析，我们可以识别出大肠杆菌核糖核苷酸还原酶基本 Y \(_{122}\)自由基中H \(^{\upbeta _2}\)耦合的特征，并用自由基构象的分布对其进行建模。在这里，我们证明了这种分析可以扩展到全角\(^1\)H ENDOR 光谱包含较大的 H \(^{\upbeta _1}\)耦合。H \(^{\upbeta _2}\)和 H \(^{\upbeta _1}\)偶联通过环二面体相互关联，并报告氨基酸构象。263 GHz ENDOR 数据分批获取而不是平均，并通过新的“漂移模型”进行数据处理，可以重建具有统计意义的置信区间的 ENDOR 光谱，并将它们与基线失真分开。使用环二面角分布的光谱模拟证实了构象分布的存在，这与之前对 H \(^{\upbeta _2}\)耦合的分析一致。分析得到了 94 GHz \(^2\)氘代 Y \(_{122}^\bullet\) 的H ENDOR 。这些研究为更详细地研究酪氨酰自由基的低人口状态提供了一个起点。