Site-directed spin labeling has enabled protein structure determination using electron spin resonance pulsed dipolar spectroscopy (PDS). Small details in a distance distribution can be key to understanding important protein structure–function relationships. A major challenge has been to differentiate unimodal and overlapped multimodal distance distributions. They often yield similar distributions and dipolar signals. Current model-free distance reconstruction techniques, such as Srivastava-Freed singular value decomposition and Tikhonov regularization, can suppress these small features in uncertainty and/or error bounds, despite being present. In this work, we demonstrate that continuous wavelet transform (CWT) can distinguish PDS signals from unimodal and multimodal distance distributions. We show that periodicity in CWT representation reflects unimodal distributions, which is masked for multimodal cases. This work is meant as a precursor to a cross-validation technique, which could indicate the modality of the distance distribution.

定点自旋标记使利用电子自旋共振脉冲偶极光谱 (PDS) 确定蛋白质结构成为可能。距离分布中的小细节可能是理解重要的蛋白质结构-功能关系的关键。一个主要挑战是区分单峰和重叠多峰距离分布。它们通常会产生相似的分布和偶极信号。当前的无模型距离重建技术，例如 Srivastava-Freed 奇异值分解和 Tikhonov 正则化，可以抑制不确定性和/或误差范围内的这些小特征，尽管存在。在这项工作中，我们证明连续小波变换 (CWT) 可以区分 PDS 信号与单峰和多峰距离分布。我们表明，CWT 表示中的周期性反映了单峰分布，这在多峰情况下被掩盖了。这项工作是交叉验证技术的先驱，可以表明距离分布的形态。