Complex portal 2025: predicted human complexes and enhanced visualisation tools for the comparison of orthologous and paralogous complexes.

IF 16.6 2区生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

Nucleic Acids Research Pub Date : 2024-11-18 DOI:10.1093/nar/gkae1085

Sucharitha Balu, Susie Huget, Juan Jose Medina Reyes, Eliot Ragueneau, Kalpana Panneerselvam, Samantha N Fischer, Erin R Claussen, Savvas Kourtis, Colin W Combe, Birgit H M Meldal, Livia Perfetto, Juri Rappsilber, Georg Kustatscher, Kevin Drew, Sandra Orchard, Henning Hermjakob

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引用次数: 0

Abstract

The Complex Portal (www.ebi.ac.uk/complexportal) is a manually curated reference database for molecular complexes. It is a unifying web resource linking aggregated data on composition, topology and the function of macromolecular complexes from 28 species. In addition to significantly extending the number of manually curated complexes, we have massively extended the coverage of the human complexome through the incorporation of high confidence assemblies predicted by machine-learning algorithms trained on large-scale experimental data. The current content of the portal comprising 2150 human complexes has been augmented by 14 964 machine-learning (ML) predicted complexes from hu.MAP3.0. We have refactored the website to enable easy search and filtering of these different classes of protein complexes and have implemented the Complex Navigator, a visualisation tool to facilitate comparison of related complexes in the context of orthology or paralogy. We have embedded the Rhea reaction visualisation tool into the website to enable users to view the catalytic activity of enzyme complexes.

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复合物门户网站 2025：预测的人类复合物以及用于比较同源和旁系复合物的增强型可视化工具。

复合体门户网站（www.ebi.ac.uk/complexportal）是一个人工编辑的分子复合体参考数据库。它是一个统一的网络资源，链接了 28 个物种的大分子复合物的组成、拓扑结构和功能的汇总数据。除了大幅增加人工整理的复合物数量外，我们还通过纳入根据大规模实验数据训练的机器学习算法预测的高置信度组合，大规模扩展了人类复合物组的覆盖范围。hu.MAP3.0 中的 14 964 个机器学习（ML）预测的复合体增加了门户网站目前包含的 2150 个人类复合体的内容。我们对网站进行了重构，以方便搜索和过滤这些不同类别的蛋白质复合物，并实施了 "复合物导航器"（Complex Navigator），这是一种可视化工具，便于在选系或旁系的背景下比较相关复合物。我们将雷亚反应可视化工具嵌入网站，使用户能够查看酶复合物的催化活性。

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

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.