AlphaFold 蛋白质结构数据库：用高精度模型极大地扩展蛋白质序列空间的结构覆盖范围。

European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK.

DeepMind, London, UK.

Nucleic Acids Res. 2022 Jan 7;50(D1):D439-D444. doi: 10.1093/nar/gkab1061.

The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) is an openly accessible, extensive database of high-accuracy protein-structure predictions. Powered by AlphaFold v2.0 of DeepMind, it has enabled an unprecedented expansion of the structural coverage of the known protein-sequence space. AlphaFold DB provides programmatic access to and interactive visualization of predicted atomic coordinates, per-residue and pairwise model-confidence estimates and predicted aligned errors. The initial release of AlphaFold DB contains over 360,000 predicted structures across 21 model-organism proteomes, which will soon be expanded to cover most of the (over 100 million) representative sequences from the UniRef90 data set.

AlphaFold 蛋白质结构数据库（AlphaFold DB，https://alphafold.ebi.ac.uk）是一个开放获取的、包含高精度蛋白质结构预测的广泛数据库。它由 DeepMind 的 AlphaFold v2.0 提供支持，实现了已知蛋白质序列空间结构覆盖范围的空前扩展。AlphaFold DB 提供对预测原子坐标、残基和对模型置信度估计以及预测对齐误差的程序访问和交互式可视化。AlphaFold DB 的初始版本包含超过 36 万个跨 21 个模式生物蛋白质组的预测结构，这些结构将很快扩展到涵盖 UniRef90 数据集的大多数（超过 1 亿）代表性序列。