Roy Aritro Sinha, Freed Jack H, Srivastava Madhur
Department of Chemistry and Chemical Biology, Cornell University, Baker Laboratory, Ithaca, 14853, NY, USA.
National Biomedical Resource for Advanced ESR Spectroscopy, Cornell University, Baker Laboratory, Ithaca, 14853, NY, USA.
Res Sq. 2023 Aug 4:rs.3.rs-3216615. doi: 10.21203/rs.3.rs-3216615/v1.
Site directed spin labeling has enabled protein structure determination using electron spin resonance (ESR) 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 (SF-SVD) 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.
定点自旋标记技术已能够利用电子自旋共振（ESR）脉冲偶极光谱法（PDS）来确定蛋白质结构。距离分布中的微小细节可能是理解重要蛋白质结构 - 功能关系的关键。一个主要挑战是区分单峰和重叠的多峰距离分布。它们常常产生相似的分布和偶极信号。当前诸如斯里瓦斯塔瓦 - 弗里德奇异值分解（SF - SVD）和蒂霍诺夫正则化等无模型距离重建技术，尽管这些小特征存在，但能够在不确定性和/或误差范围内抑制它们。在这项工作中，我们证明连续小波变换（CWT）可以区分来自单峰和多峰距离分布的PDS信号。我们表明，CWT表示中的周期性反映了单峰分布，而在多峰情况下这种周期性会被掩盖。这项工作旨在作为一种交叉验证技术的先导，该技术可以指示距离分布的模式。
