Highly accurate protein structure prediction for the human proteome.
Highly accurate protein structure prediction for the human proteome.
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DOI：
10.1038/s41586-021-03828-1
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发表时间：
2021-08
期刊：
影响因子：
64.8
通讯作者：
Hassabis D
中科院分区：
文献类型：
--
作者：
Tunyasuvunakool K;Adler J;Wu Z;Green T;Zielinski M;Žídek A;Bridgland A;Cowie A;Meyer C;Laydon A;Velankar S;Kleywegt GJ;Bateman A;Evans R;Pritzel A;Figurnov M;Ronneberger O;Bates R;Kohl SAA;Potapenko A;Ballard AJ;Romera-Paredes B;Nikolov S;Jain R;Clancy E;Reiman D;Petersen S;Senior AW;Kavukcuoglu K;Birney E;Kohli P;Jumper J;Hassabis D
蛋白质结构可以提供宝贵的信息，包括生物学过程的推理，以及在数十年的努力之后，诸如基于结构的药物发展或靶向诱变之类的干预措施。在这里，我们通过应用最先进的机器学习方法（几乎整个人类蛋白质（98.5％的人类蛋白质）覆盖了58％的残留物，其中一个子集（所有残留物的36％）具有很高的信心。模型并使用它们来解释数据集，确定强大的多域预测以及可能是无序的区域。预测可用于产生生物学假设。
Alphafold用于预测人蛋白质组几乎所有蛋白质的结构 - 高信心预测结构的可用性可以从结构的角度实现新的投资途径。
Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17% of the total residues in human protein sequences are covered by an experimentally determined structure. Here we markedly expand the structural coverage of the proteome by applying the state-of-the-art machine learning method, AlphaFold, at a scale that covers almost the entire human proteome (98.5% of human proteins). The resulting dataset covers 58% of residues with a confident prediction, of which a subset (36% of all residues) have very high confidence. We introduce several metrics developed by building on the AlphaFold model and use them to interpret the dataset, identifying strong multi-domain predictions as well as regions that are likely to be disordered. Finally, we provide some case studies to illustrate how high-quality predictions could be used to generate biological hypotheses. We are making our predictions freely available to the community and anticipate that routine large-scale and high-accuracy structure prediction will become an important tool that will allow new questions to be addressed from a structural perspective. AlphaFold is used to predict the structures of almost all of the proteins in the human proteome—the availability of high-confidence predicted structures could enable new avenues of investigation from a structural perspective.
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影响因子：
2.9
作者：
Haas J;Barbato A;Behringer D;Studer G;Roth S;Bertoni M;Mostaguir K;Gumienny R;Schwede T
通讯作者：
Schwede T
影响因子：
14.9
作者：
Gene Ontology Consortium
通讯作者：
Gene Ontology Consortium
影响因子：
5.6
作者：
Guardino KM;Sheftic SR;Slattery RE;Alexandrescu AT
通讯作者：
Alexandrescu AT
影响因子：
15
作者：
Bhowmick A;Brookes DH;Yost SR;Dyson HJ;Forman-Kay JD;Gunter D;Head-Gordon M;Hura GL;Pande VS;Wemmer DE;Wright PE;Head-Gordon T
通讯作者：
Head-Gordon T
影响因子：
14.9
作者：
wwPDB consortium
通讯作者：
wwPDB consortium