Department of Chemistry, University of Washington, Seattle, Washington.
Department of Chemistry, University of Washington, Seattle, Washington.
Biophys J. 2022 Sep 20;121(18):3508-3519. doi: 10.1016/j.bpj.2022.08.002. Epub 2022 Aug 10.
Site-directed spin-labeling electron paramagnetic resonance spectroscopy is a powerful technique for the investigation of protein structure and dynamics. Accurate spin-label modeling methods are essential to make full quantitative use of site-directed spin-labeling electron paramagnetic resonance data for protein modeling and model validation. Using a set of double electron-electron resonance data from seven different site pairs on maltodextrin/maltose-binding protein under two different conditions using five different spin labels, we compare the ability of two widely used spin-label modeling methods, based on accessible volume sampling and rotamer libraries, to predict experimental distance distributions. We present a spin-label modeling approach inspired by canonical side-chain modeling methods and compare modeling accuracy with the established methods.
定点自旋标记电子顺磁共振波谱学是研究蛋白质结构和动力学的一种强大技术。准确的自旋标记建模方法对于充分利用定点自旋标记电子顺磁共振数据进行蛋白质建模和模型验证至关重要。我们使用一组来自麦芽糖结合蛋白在两种不同条件下的七个不同位点对的双电子电子共振数据，使用五种不同的自旋标记物，比较了两种广泛使用的基于可及体积采样和构象文库的自旋标记建模方法预测实验距离分布的能力。我们提出了一种受经典侧链建模方法启发的自旋标记建模方法，并将建模准确性与已有方法进行了比较。
