Pfam 蛋白质家族数据库：拥抱人工智能/ML

IF 16.6 2区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Nucleic Acids Research Pub Date : 2024-11-14 DOI:10.1093/nar/gkae997

Typhaine Paysan-Lafosse, Antonina Andreeva, Matthias Blum, Sara Rocio Chuguransky, Tiago Grego, Beatriz Lazaro Pinto, Gustavo A Salazar, Maxwell L Bileschi, Felipe Llinares-López, Laetitia Meng-Papaxanthos, Lucy J Colwell, Nick V Grishin, R Dustin Schaeffer, Damiano Clementel, Silvio C E Tosatto, Erik Sonhammer, Valerie Wood, Alex Bateman

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引用次数: 0

摘要

Pfam 蛋白质家族数据库是用于基因组注释和蛋白质结构与功能分析的蛋白质结构域和家族的综合集合 (https://www.ebi.ac.uk/interpro/)。本次更新介绍了 Pfam 自 2020 年以来的主要发展情况，包括 Pfam 网站的退役和与 InterPro 的整合、与 ECOD 结构分类的协调，以及对元基因组、微蛋白和含重复家族的扩展整理。我们重点介绍了如何利用 AlphaFold 结构预测来完善结构域边界和识别新结构域。我们还介绍了通过对 AlphaFold 模型进行大规模序列相似性分析而发现的新科属。我们还详细介绍了 Pfam-N 的开发情况，它利用深度学习扩大了科的覆盖范围，与标准 Pfam 相比，UniProtKB 的覆盖范围增加了 8.8%。我们讨论了更频繁地发布与 InterPro 集成的 Pfam 的计划，以及人工智能进一步协助整理工作的潜力。尽管最近取得了一些进展，但仍有许多蛋白质家族有待分类，Pfam 将继续努力实现蛋白质领域的全面覆盖。

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The Pfam protein families database: embracing AI/ML

The Pfam protein families database is a comprehensive collection of protein domains and families used for genome annotation and protein structure and function analysis (https://www.ebi.ac.uk/interpro/). This update describes major developments in Pfam since 2020, including decommissioning the Pfam website and integration with InterPro, harmonization with the ECOD structural classification, and expanded curation of metagenomic, microprotein and repeat-containing families. We highlight how AlphaFold structure predictions are being leveraged to refine domain boundaries and identify new domains. New families discovered through large-scale sequence similarity analysis of AlphaFold models are described. We also detail the development of Pfam-N, which uses deep learning to expand family coverage, achieving an 8.8% increase in UniProtKB coverage compared to standard Pfam. We discuss plans for more frequent Pfam releases integrated with InterPro and the potential for artificial intelligence to further assist curation. Despite recent advances, many protein families remain to be classified, and Pfam continues working toward comprehensive coverage of the protein universe.

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来源期刊

Nucleic Acids Research 生物-生化与分子生物学

CiteScore

27.10

自引率

4.70%

发文量

1057

审稿时长

2 months

期刊介绍： Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.