AlphaFold3 是由 DeepMind 公司于 2024 年开发的一款革命性的人工智能程序，它在蛋白质结构预测领域取得了重大突破。相关论文成果为「Accurate structure prediction of biomolecular interactions with AlphaFold 3」，并获得诺贝尔奖。 该数据库包含 AlphaFold 3 依赖的大量蛋白质和 RNA 数据库，包括 BFD small 、 MGnify 、 PDB 、 PDB seqres 、 UniProt 、 UniRef90 、 NT 、 RFam 和 RNACentral 这 9 个数据库。 注意：依赖数据库解压后多达 630 GB，为了防止下载过程断开，请确保有足够的硬盘空间、带宽和时间来下载这些数据库。

Citation

@article{Abramson2024, author = {Abramson, Josh and Adler, Jonas and Dunger, Jack and Evans, Richard and Green, Tim and Pritzel, Alexander and Ronneberger, Olaf and Willmore, Lindsay and Ballard, Andrew J. and Bambrick, Joshua and Bodenstein, Sebastian W. and Evans, David A. and Hung, Chia-Chun and O’Neill, Michael and Reiman, David and Tunyasuvunakool, Kathryn and Wu, Zachary and Žemgulytė, Akvilė and Arvaniti, Eirini and Beattie, Charles and Bertolli, Ottavia and Bridgland, Alex and Cherepanov, Alexey and Congreve, Miles and Cowen-Rivers, Alexander I. and Cowie, Andrew and Figurnov, Michael and Fuchs, Fabian B. and Gladman, Hannah and Jain, Rishub and Khan, Yousuf A. and Low, Caroline M. R. and Perlin, Kuba and Potapenko, Anna and Savy, Pascal and Singh, Sukhdeep and Stecula, Adrian and Thillaisundaram, Ashok and Tong, Catherine and Yakneen, Sergei and Zhong, Ellen D. and Zielinski, Michal and Žídek, Augustin and Bapst, Victor and Kohli, Pushmeet and Jaderberg, Max and Hassabis, Demis and Jumper, John M.}, journal = {Nature}, title = {Accurate structure prediction of biomolecular interactions with AlphaFold 3}, year = {2024}, volume = {630}, number = {8016}, pages = {493–-500}, doi = {10.1038/s41586-024-07487-w} }