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bioRxiv · 10.1101/2023.01.03.522554

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

Pan, Y.·Li, R.·Li, W.·Lv, L.·Guan, J.·Zhou, S.
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Abstract

A fundamental principle of biology is that proteins tend to form complexes to play significant 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 and biological mechanisms. To fill this gap, we built 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 works, our method achieves outstanding performance on both test and independent sets. Furthermore, with HPC-Atlas we identified 751 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.

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Pan, Y., Li, R., Li, W., Lv, L., Guan, J., Zhou, S.. 2023-01-04. HPC-Atlas: Computationally Constructing A Comprehensive Atlas of Human Protein Complexes. https://doi.org/10.1101/2023.01.03.522554

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