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Article

CoVM2: Molecular Biological Data Integration of SARS-CoV-2 Proteins in a Macro-to-Micro Method

1
Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China
2
Chu Kochen Honors College, Zhejiang University, Hangzhou 310058, China
3
Institute of Hematology, Zhejiang University School of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
Academic Editors: Zhiliang Ji, Ruhong Zhou and Xuanyu Meng
Biomolecules 2022, 12(8), 1067; https://doi.org/10.3390/biom12081067
Received: 8 June 2022 / Revised: 27 July 2022 / Accepted: 29 July 2022 / Published: 2 August 2022
The COVID-19 pandemic has been a major public health event since 2020. Multiple variant strains of SARS-CoV-2, the causative agent of COVID-19, were detected based on the mutation sites in their sequences. These sequence mutations may lead to changes in the protein structures and affect the binding states of SARS-CoV-2 and human proteins. Experimental research on SARS-CoV-2 has accumulated a large amount of structural data and protein-protein interactions (PPIs), but the studies on the SARS-CoV-2–human PPI networks lack integration of physical associations with possible protein docking information. In addition, the docking structures of variant viral proteins with human receptor proteins are still insufficient. This study constructed SARS-CoV-2–human protein–protein interaction network with data integration methods. Crystal structures were collected to map the interaction pairs. The pairs of direct interactions and physical associations were selected and analyzed for variant docking calculations. The study examined the structures of spike (S) glycoprotein of variants Delta B.1.617.2, Omicron BA.1, and Omicron BA.2. The calculated docking structures of S proteins and potential human receptors were obtained. The study integrated binary protein interactions with 3D docking structures to fulfill an extended view of SARS-CoV-2 proteins from a macro- to micro-scale. View Full-Text
Keywords: SARS-CoV-2; virus–host interactions; protein structure docking; binding affinity; molecular biology; data integration SARS-CoV-2; virus–host interactions; protein structure docking; binding affinity; molecular biology; data integration
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MDPI and ACS Style

Chen, H.; Hu, X.; Hu, Y.; Zhou, J.; Chen, M. CoVM2: Molecular Biological Data Integration of SARS-CoV-2 Proteins in a Macro-to-Micro Method. Biomolecules 2022, 12, 1067. https://doi.org/10.3390/biom12081067

AMA Style

Chen H, Hu X, Hu Y, Zhou J, Chen M. CoVM2: Molecular Biological Data Integration of SARS-CoV-2 Proteins in a Macro-to-Micro Method. Biomolecules. 2022; 12(8):1067. https://doi.org/10.3390/biom12081067

Chicago/Turabian Style

Chen, Hongjun, Xiaotian Hu, Yanshi Hu, Jiawen Zhou, and Ming Chen. 2022. "CoVM2: Molecular Biological Data Integration of SARS-CoV-2 Proteins in a Macro-to-Micro Method" Biomolecules 12, no. 8: 1067. https://doi.org/10.3390/biom12081067

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