The prediction of the three-dimensional (3D) structure of proteins from the amino acid sequence made a stunning breakthrough reaching atomic accuracy. Using the neural network-based method AlphaFold2, 3D structures of almost the entire human proteome have been predicted and made available (https://www.alphafold.ebi.ac.uk). To gain insight into how well AlphaFold2 structures represent the conformation of proteins in solution, I here compare the AlphaFold2 structures of selected small proteins with their 3D structures that were determined by nuclear magnetic resonance (NMR) spectroscopy. Proteins were selected for which the 3D solution structures were determined on the basis of a very large number of distance restraints and residual dipolar couplings and are thus some of the best-resolved solution structures of proteins to date. The quality of the backbone conformation of the AlphaFold2 structures is assessed by fitting a large set of experimental residual dipolar couplings (RDCs). The analysis shows that experimental RDCs fit extremely well to the AlphaFold2 structures predicted for GB3, DinI, and ubiquitin. In the case of GB3, the accuracy of the AlphaFold2 structure even surpasses that of a 1.1 Å crystal structure. Fitting of experimental RDCs furthermore allows identification of AlphaFold2 structures that are best representative of the protein's conformation in solution as seen for the EF hands of the N-terminal domain of Ca²⁺-ligated calmodulin. Taken together, the analysis shows that structures predicted by AlphaFold2 can be highly representative of the solution conformation of proteins. The combination of AlphaFold2 structures with RDCs promises to be a powerful approach to study structural changes in proteins.

中文翻译：

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AlphaFold2 结构的核磁共振鹰眼视图

从氨基酸序列预测蛋白质的三维 (3D) 结构取得了惊人的突破，达到了原子精度。使用基于神经网络的方法 AlphaFold2，几乎整个人类蛋白质组的 3D 结构已被预测并可用（https://www.alphafold.ebi.ac.uk）。为了深入了解 AlphaFold2 结构如何很好地代表溶液中蛋白质的构象，我在这里将选定的小蛋白质的 AlphaFold2 结构与其核磁共振 (NMR) 光谱确定的 3D 结构进行了比较。所选择的蛋白质的 3D 溶液结构是根据大量距离限制和残余偶极耦合确定的，因此是迄今为止解析度最高的蛋白质溶液结构之一。AlphaFold2 结构的骨架构象的质量是通过拟合大量实验残余偶极耦合 (RDC) 来评估的。分析表明，实验性 RDC 非常适合预测的 GB3、DinI 和泛素的 AlphaFold2 结构。在 GB3 的情况下，AlphaFold2 结构的精度甚至超过了 1.1 Å 晶体结构的精度。实验 RDC 的拟合还允许鉴定最能代表溶液中蛋白质构象的 AlphaFold2 结构，如 Ca 的 N 端域的 EF 手所见 DinI 和泛素。在 GB3 的情况下，AlphaFold2 结构的精度甚至超过了 1.1 Å 晶体结构的精度。实验 RDC 的拟合还允许鉴定最能代表溶液中蛋白质构象的 AlphaFold2 结构，如 Ca 的 N 端域的 EF 手所见 DinI 和泛素。在 GB3 的情况下，AlphaFold2 结构的精度甚至超过了 1.1 Å 晶体结构的精度。实验 RDC 的拟合还允许鉴定最能代表溶液中蛋白质构象的 AlphaFold2 结构，如 Ca 的 N 端域的 EF 手所见^2+-连接的钙调蛋白。总之，分析表明 AlphaFold2 预测的结构可以高度代表蛋白质的溶液构象。AlphaFold2 结构与 RDC 的结合有望成为研究蛋白质结构变化的有力方法。