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毫无疑问，2021 年人类在蛋白质领域的探索取得了前所未有的成就。
在 2021 年 7 月 15 日，谷歌的 DeepMind 团队以及华盛顿大学的 Baker 团队，分别在 Nature 和 Science 两本顶刊杂志上发布并开源了蛋白质结构预测工具 AlphaFold2 与 RoseTTAFold。
这对于蛋白质领域是无疑是重磅进展。在之后的研究中，来自世界各地的科学家团队使用开源的工具对未知蛋白进行探索，同时也不断验证了新工具的稳健性。更有团队以开源的蛋白质结构预测工具为基准，开发了蛋白互作预测工具。
ScienceAI 认为，2021年蛋白质结构预测所取得的进展，是分子生物学发展的一座里程碑。
以下是 ScienceAI 2021 年蛋白质专题报道的年度总结。
友情提示：点击小标题可直接访问文章
一天之内，两大 AI 预测蛋白结构算法开源，分别登上 Nature、Science
Nature | Highly accurate protein structure prediction with AlphaFold
论文链接：https://www.nature.com/articles/s41586-021-03819-2
开源地址：https://github.com/deepmind/alphafold
Science | Accurate prediction of protein structures and interactions using a three-track neural network
论文链接：https://science.sciencemag.org/content/early/2021/07/14/science.abj8754
开源地址：https://github.com/RosettaCommons/RoseTTAFold
AlphaFold 再登 Nature！预测确定 98.5% 所有人类蛋白结构，数据库全部免费开放
Nature | Highly accurate protein structure prediction for the human proteome
论文链接：https://www.nature.com/articles/s41586-021-03828-1
Nature | Artificial intelligence powers protein-folding predictions
论文链接：https://www.nature.com/articles/d41586-021-03499-y
生物计算专家超细致解读 AlphaFold2 论文：模型架构及应用
来自哥伦比亚大学欧文医学中心 Mohammed AlQuraishi 的个人博客
原文链接：https://moalquraishi.wordpress.com/2021/07/25/the-alphafold2-method-paper-a-fount-of-good-ideas/
网红教授发 Nature 品评 AlphaFold2，蛋白质结构预测将彻底改变
Nature | Protein-structure prediction revolutionized
论文链接：https://www.nature.com/articles/d41586-021-02265-4
AlphaFold 2 对蛋白结构研究领域的冲击有多大，听听这五位专家怎么说
来自机器之心策划的《AlphaFold 2「能」与「不能」》知识分享活动
视频回放链接：https://jmq.h5.xeknow.com/s/2ZtoeT
Nature社论：AlphaFold 为生命科学带来了什么？开源的技术和未来的方向
Nature | Artificial intelligence in structural biology is here to stay
论文链接：https://www.nature.com/articles/d41586-021-02037-0
借助 AlphaFold2 对噬菌体粘附装置的结构和拓扑进行解析
Microorganisms | Structure and Topology Prediction of Phage Adhesion Devices Using AlphaFold2: The Case of Two Oenococcus oeni Phages
论文链接：https://www.mdpi.com/2076-2607/9/10/2151/htm
已开源新工具：在 AlphaFold 建模的基础上，解析蛋白质的糖基化修饰
Nature Structural & Molecular Biology | The case for post-predictional modifications in the AlphaFold Protein Structure Database
数据链接：https://zenodo.org/record/5564681
论文链接：https://www.nature.com/articles/s41594-021-00680-9
人工智能揭示核孔结构，再次证明 AlphaFold 和 RoseTTAfold 预测的可靠性
bioRxiv 预印平台 | Artificial intelligence reveals nuclear pore complexity
论文链接：https://www.biorxiv.org/content/10.1101/2021.10.26.465776v1.full.pdf
预测结果与实验数据基本一致，AlphaFold2 应用于研究蛋白活化以及相互作用
Molecular Reproduction and Development | Using machine learning to study protein–protein interactions: From the uromodulin polymer to egg zona pellucida filaments
论文链接：https://onlinelibrary.wiley.com/doi/10.1002/mrd.23538
Nature Structural & Molecular Biology | AlphaFold2 and the future of structural biology
论文链接：https://www.nature.com/articles/s41594-021-00650-1
Nature Biotechnology | The 3D protein deluge
论文链接：https://www.nature.com/articles/s41587-021-01029-9
无需「协同进化」信息，芝加哥许锦波团队最新研究登上Nature子刊
Nature Machine Intelligence | Improved protein structure prediction by deep learning irrespective of co-evolution information
论文链接：https://www.nature.com/articles/s42256-021-00348-5
Nature Computational Science | Fast and effective protein model refinement using deep graph neural networks
开源地址：http://raptorx.uchicago.edu/
论文链接：https://www.nature.com/articles/s43588-021-00098-9
Science | Computed structures of core eukaryotic protein complexes
论文链接：https://www.science.org/doi/10.1126/science.abm4805
Bioinformatics | PhosIDN: an integrated deep neural network for improving protein phosphorylation site prediction by combining sequence and protein–protein interaction information
开源地址：https://github.com/ustchangyuanyang/PhosIDN
论文链接：https://academic.oup.com/bioinformatics/article/37/24/4668/6329824
Bioinformatics | Transfer learning via multi-scale convolutional neural layers for human–virus protein–protein interaction prediction
开源地址：https://github.com/XiaodiYangCAU/TransPPI/
论文链接：https://academic.oup.com/bioinformatics/article-abstract/37/24/4771/6323357?redirectedFrom=fulltext
Bioinformatics | DeepTrio: a ternary prediction system for protein–protein interaction using mask multiple parallel convolutional neural networks
开源地址：https://github.com/huxiaoti/deeptrio.git
论文链接：https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btab737/6409848?redirectedFrom=fulltext
Bioinformatics | pyconsFold: a fast and easy tool for modeling and docking using distance predictions
开源地址：https://github.com/johnlamb/pyconsfold
论文链接：https://academic.oup.com/bioinformatics/article/37/21/3959/6317824
Nature Machine Intelligence | A geometric deep learning approach to predict binding conformations of bioactive molecules
论文链接：https://www.nature.com/articles/s42256-021-00409-9
8张RTX3090，效果媲美AlphaFold2，国产蛋白结构预测平台TRFold排名全球第二
来自对天壤团队的采访
Science Advances | The Human Proteoform Project: Defining the human proteome
论文链接：https://www.science.org/doi/10.1126/sciadv.abk0734
Nature Communications | ECNet is an evolutionary context-integrated deep learning framework for protein engineering
论文链接：https://www.nature.com/articles/s41467-021-25976-8
Nature Methods | Neural networks learn the motions of molecular machines
论文链接：https://www.nature.com/articles/s41592-021-01235-y
Nature | De novo protein design by deep network hallucination
论文链接：https://www.nature.com/articles/s41586-021-04184-w
Bioinformatics | EDCNN: identification of genome-wide RNA-binding proteins using evolutionary deep convolutional neural network
论文链接：https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btab739/6409850?redirectedFrom=fulltext
Nature Biomedical Engineering | Mining for encrypted peptide antibiotics in the human proteome
论文链接：https://www.nature.com/articles/s41551-021-00801-1
上科大研究登Nature子刊，深度学习更快、更深入地进行磷酸化蛋白质组分析
Nature Communications | DeepPhospho accelerates DIA phosphoproteome profiling through in silico library generation
论文链接：https://www.nature.com/articles/s41467-021-26979-1
PLOS BIOLOGY | Deep learning allows genome-scale prediction of Michaelis constants from structural features
论文链接：https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3001402
Nature Biotechnology | Multiplexed direct detection of barcoded protein reporters on a nanopore array
论文链接：https://www.nature.com/articles/s41587-021-01002-6
PNAS | Single-particle diffusional fingerprinting: A machine-learning framework for quantitative analysis of heterogeneous diffusion
论文链接：https://www.pnas.org/content/118/31/e2104624118#abstract-2
使用 3D 卷积神经网络检测蛋白质-肽结合位点，以启动肽药物发现
Journal of Chemical Information and Modeling | Protein−Peptide Binding Site Detection Using 3D Convolutional Neural Networks
论文链接：https://pubs.acs.org/doi/10.1021/acs.jcim.1c00475
AI伦理领袖、AlphaFold作者上榜！Nature发布「2021十大科学人物」
原文链接：https://www.nature.com/immersive/d41586-021-03621-0/index.html#section-wEfZ0Jxqu4
原文链接：https://www.science.org/content/article/breakthrough-2021#section_breakthrough
