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

Hongjun Chen; Xiaotian Hu; Yanshi Hu; Jiawen Zhou; Ming Chen

doi:10.3390/biom12081067

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

Biomolecules. 2022 Aug 2;12(8):1067. doi: 10.3390/biom12081067.

Authors

Hongjun Chen¹, Xiaotian Hu¹, Yanshi Hu¹, Jiawen Zhou², Ming Chen^{1

3}

Affiliations

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.

Abstract

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.

Keywords: SARS-CoV-2; binding affinity; data integration; molecular biology; protein structure docking; virus–host interactions.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

COVID-19*
Humans
Mutation
Pandemics
SARS-CoV-2* / genetics
Viral Proteins

Substances

Viral Proteins

Supplementary concepts

SARS-CoV-2 variants

Grants and funding

This research was funded by the National Key Research and Development Program of China [2016YFA0501704, 2018YFC0310602]; the National Natural Sciences Foundation of China [31771477, 32070677]; the 151 talent project of Zhejiang Province (first level), Jiangsu Collaborative Innovation Center for Modern Crop Production and Collaborative Innovation Center for Modern Crop Production co-sponsored by province and ministry.