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

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, we require 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 also 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 integrate new protein data sources for identifying biologically meaningful protein complexes, but also a valuable resource for exploring new biological findings. The HPC-Atlas webserver is freely available at http://www.yulpan.top/HPC-Atlas.

PCGAN: a generative approach for protein complex identification from protein interaction networks

“…In the past decade, a number of computational methods have been proposed to identify PCs from PINs ( Jiang and Singh 2010 , Kenley and Cho 2011 , Nepusz et al 2012 , Wu et al 2021b , Pan et al 2023 ). Most of them employ clustering algorithms by treating PCs as dense subnetworks or subgraphs in PINs ( Kenley and Cho 2011 , Nepusz et al 2012 , Wu et al 2021b ).…”

Function, drug resistance and prognostic effect of AKR1C2 in human cancer

“…The protein encoded by this gene is 37 kDa, which is mainly distributed in the cytoplasm of cells and is closely related to AKR1C1, AKR1C3, and AKR1C4 (Figures 1A, 1B) [12,13]. High protein expression of AKR1C2 can be detected in human liver, stomach, and bladder tissue [14]. However, it cannot be detected in some tissues such as placenta, spleen, bone marrow, and lymph nodes [14].…”

“…High protein expression of AKR1C2 can be detected in human liver, stomach, and bladder tissue [14]. However, it cannot be detected in some tissues such as placenta, spleen, bone marrow, and lymph nodes [14].…”