Exploring structural diversity across the protein universe with The Encyclopedia of Domains

IF 44.7 1区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Science Pub Date : 2024-11-01 DOI:10.1126/science.adq4946

Andy M. Lau, Nicola Bordin, Shaun M. Kandathil, Ian Sillitoe, Vaishali P. Waman, Jude Wells, Christine A. Orengo, David T. Jones

引用次数: 0

Abstract

The AlphaFold Protein Structure Database (AFDB) contains more than 214 million predicted protein structures composed of domains, which are independently folding units found in multiple structural and functional contexts. Identifying domains can enable many functional and evolutionary analyses but has remained challenging because of the sheer scale of the data. Using deep learning methods, we have detected and classified every domain in the AFDB, producing The Encyclopedia of Domains. We detected nearly 365 million domains, over 100 million more than can be found by sequence methods, covering more than 1 million taxa. Reassuringly, 77% of the nonredundant domains are similar to known superfamilies, greatly expanding representation of their domain space. We uncovered more than 10,000 new structural interactions between superfamilies and thousands of new folds across the fold space continuum.

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通过《结构域百科全书》探索整个蛋白质宇宙的结构多样性

AlphaFold 蛋白结构数据库（AFDB）包含超过 2.14 亿个由结构域组成的预测蛋白质结构，结构域是在多种结构和功能环境中发现的独立折叠单元。识别结构域可以进行许多功能和进化分析，但由于数据规模庞大，识别结构域仍然具有挑战性。利用深度学习方法，我们对 AFDB 中的每个结构域进行了检测和分类，编写了《结构域百科全书》（The Encyclopedia of Domains）。我们检测到了近 3.65 亿个域，比序列方法检测到的域多 1 亿多个，涵盖 100 多万个类群。令人欣慰的是，77% 的非冗余结构域与已知超家族相似，大大扩展了其结构域空间的代表性。我们在超家族之间发现了 10,000 多种新的结构相互作用，并在折叠空间连续体中发现了数千种新的折叠。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Science 综合性期刊-综合性期刊

CiteScore

61.10

自引率

0.90%

发文量

审稿时长

2.1 months

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