Tessmer Maxx H, Stoll Stefan
Department of Chemistry, University of Washington, Seattle, Washington, USA; email:
Annu Rev Biophys. 2025 May;54(1):35-57. doi: 10.1146/annurev-biophys-030524-013431. Epub 2024 Dec 17.
Double electron-electron resonance (DEER) combined with site-directed spin labeling can provide distance distributions between selected protein residues to investigate protein structure and conformational heterogeneity. The utilization of the full quantitative information contained in DEER data requires effective protein and spin label modeling methods. Here, we review the application of DEER data to protein modeling. First, we discuss the significance of spin label modeling for accurate extraction of protein structural information and review the most popular label modeling methods. Next, we review several important aspects of protein modeling with DEER, including site selection, how DEER restraints are applied, common artifacts, and the unique potential of DEER data for modeling structural ensembles and conformational landscapes. Finally, we discuss common applications of protein modeling with DEER data and provide an outlook.
双电子-电子共振(DEER)结合定点自旋标记能够提供选定蛋白质残基之间的距离分布,以研究蛋白质结构和构象异质性。有效利用DEER数据中包含的完整定量信息需要有效的蛋白质和自旋标记建模方法。在此,我们综述了DEER数据在蛋白质建模中的应用。首先,我们讨论自旋标记建模对于准确提取蛋白质结构信息的重要性,并综述最常用的标记建模方法。接下来,我们综述利用DEER进行蛋白质建模的几个重要方面,包括位点选择、DEER约束条件的应用方式、常见伪影,以及DEER数据在构建结构集合和构象图谱方面的独特潜力。最后,我们讨论利用DEER数据进行蛋白质建模的常见应用并给出展望。