Department of Chemistry, University of Pittsburgh, 219 Parkman Avenue, Pittsburgh, PA, 15260, USA.
Chempluschem. 2024 Jan;89(1):e202300506. doi: 10.1002/cplu.202300506. Epub 2023 Oct 25.
Electron paramagnetic resonance (EPR) has become a powerful probe of conformational heterogeneity and dynamics of biomolecules. In this Review, we discuss different computational modeling techniques that enrich the interpretation of EPR measurements of dynamics or distance restraints. A variety of spin labels are surveyed to provide a background for the discussion of modeling tools. Molecular dynamics (MD) simulations of models containing spin labels provide dynamical properties of biomolecules and their labels. These simulations can be used to predict EPR spectra, sample stable conformations and sample rotameric preferences of label sidechains. For molecular motions longer than milliseconds, enhanced sampling strategies and de novo prediction software incorporating or validated by EPR measurements are able to efficiently refine or predict protein conformations, respectively. To sample large-amplitude conformational transition, a coarse-grained or an atomistic weighted ensemble (WE) strategy can be guided with EPR insights. Looking forward, we anticipate an integrative strategy for efficient sampling of alternate conformations by de novo predictions, followed by validations by systematic EPR measurements and MD simulations. Continuous pathways between alternate states can be further sampled by WE-MD including all intermediate states.
电子顺磁共振（EPR）已成为研究生物分子构象异质性和动力学的有力工具。在这篇综述中，我们讨论了不同的计算建模技术，这些技术丰富了对动力学或距离约束的 EPR 测量的解释。我们调查了各种自旋标记物，为讨论建模工具提供了背景。包含自旋标记物的模型的分子动力学（MD）模拟提供了生物分子及其标记物的动力学特性。这些模拟可用于预测 EPR 谱，获取稳定构象并获取标记侧链的构象偏好。对于大于毫秒的分子运动，增强采样策略和包含或经过 EPR 测量验证的从头预测软件能够分别有效地细化或预测蛋白质构象。为了采样大振幅构象转变，可以使用 EPR 见解来指导粗粒化或原子加权系综（WE）策略。展望未来，我们预计通过从头预测进行有效采样替代构象的综合策略，然后通过系统的 EPR 测量和 MD 模拟进行验证。通过包括所有中间状态的 WE-MD 可以进一步采样替代状态之间的连续路径。
