Biozentrum, University of Basel, Basel, Switzerland.
SIB Swiss Institute of Bioinformatics, University of Basel, Basel, Switzerland.
Nature. 2023 Oct;622(7983):646-653. doi: 10.1038/s41586-023-06622-3. Epub 2023 Sep 13.
We are now entering a new era in protein sequence and structure annotation, with hundreds of millions of predicted protein structures made available through the AlphaFold database. These models cover nearly all proteins that are known, including those challenging to annotate for function or putative biological role using standard homology-based approaches. In this study, we examine the extent to which the AlphaFold database has structurally illuminated this 'dark matter' of the natural protein universe at high predicted accuracy. We further describe the protein diversity that these models cover as an annotated interactive sequence similarity network, accessible at https://uniprot3d.org/atlas/AFDB90v4 . By searching for novelties from sequence, structure and semantic perspectives, we uncovered the β-flower fold, added several protein families to Pfam database and experimentally demonstrated that one of these belongs to a new superfamily of translation-targeting toxin-antitoxin systems, TumE-TumA. This work underscores the value of large-scale efforts in identifying, annotating and prioritizing new protein families. By leveraging the recent deep learning revolution in protein bioinformatics, we can now shed light into uncharted areas of the protein universe at an unprecedented scale, paving the way to innovations in life sciences and biotechnology.
我们现在正进入蛋白质序列和结构注释的新时代，通过 AlphaFold 数据库提供了数亿个预测的蛋白质结构。这些模型几乎涵盖了所有已知的蛋白质，包括那些使用标准同源性方法难以注释功能或假定生物学作用的蛋白质。在这项研究中，我们研究了 AlphaFold 数据库在高预测精度下在多大程度上阐明了自然蛋白质宇宙中的这种“暗物质”。我们进一步描述了这些模型所涵盖的蛋白质多样性，作为一个带有注释的交互式序列相似性网络，可在 https://uniprot3d.org/atlas/AFDB90v4 访问。通过从序列、结构和语义角度搜索新颖性，我们发现了β-花折叠，向 Pfam 数据库添加了几个蛋白质家族，并通过实验证明其中一个属于一种新的翻译靶向毒素-抗毒素系统的超家族，即 TumE-TumA。这项工作强调了在识别、注释和优先考虑新蛋白质家族方面的大规模努力的价值。通过利用蛋白质生物信息学中的深度学习革命，我们现在可以以前所未有的规模揭示蛋白质宇宙中未知的领域，为生命科学和生物技术的创新铺平道路。
