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HPC-Atlas: Computationally Constructing A Comprehensive Atlas of Human Protein Complexes.

Authors :
Pan Y
Li R
Li W
Lv L
Guan J
Zhou S
Source :
Genomics, proteomics & bioinformatics [Genomics Proteomics Bioinformatics] 2023 Oct; Vol. 21 (5), pp. 976-990. Date of Electronic Publication: 2023 Sep 18.
Publication Year :
2023

Abstract

A fundamental principle of biology is that proteins tend to form complexes to play important roles in the core functions of cells. For a complete understanding of human cellular functions, it is crucial to have a comprehensive atlas of human protein complexes. Unfortunately, we still lack such a comprehensive atlas of experimentally validated protein complexes, which prevents us from gaining a complete understanding of the compositions and functions of human protein complexes, as well as the underlying biological mechanisms. To fill this gap, we built Human Protein Complexes Atlas (HPC-Atlas), as far as we know, the most accurate and comprehensive atlas of human protein complexes available to date. We integrated two latest protein interaction networks, and developed a novel computational method to identify nearly 9000 protein complexes, including many previously uncharacterized complexes. Compared with the existing methods, our method achieved outstanding performance on both testing and independent datasets. Furthermore, with HPC-Atlas we identified 751 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-affected human protein complexes, and 456 multifunctional proteins that contain many potential moonlighting proteins. These results suggest that HPC-Atlas can serve as not only a computing framework to effectively identify biologically meaningful protein complexes by integrating multiple protein data sources, but also a valuable resource for exploring new biological findings. The HPC-Atlas webserver is freely available at http://www.yulpan.top/HPC-Atlas.<br /> (Copyright © 2023 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. Published by Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
2210-3244
Volume :
21
Issue :
5
Database :
MEDLINE
Journal :
Genomics, proteomics & bioinformatics
Publication Type :
Academic Journal
Accession number :
37730114
Full Text :
https://doi.org/10.1016/j.gpb.2023.05.001