A target prediction method to inhibit the replication process of SARS-CoV-2 via metabolic differential analysis

A target prediction method to inhibit the replication process of SARS-CoV-2 via metabolic differential analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A target prediction method to inhibit the replication process of SARS-CoV-2 via metabolic differential analysis Haoran Zheng, Yupeng Qi, Yanlong Zhao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2668079/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The emergence and rapid spread of COVID-19 has had a tremendous impact on people's lives, and it is therefore necessary to study how to treat COVID-19. SARS-CoV-2 invades and reprograms human cells, altering the host cell metabolic system to favor its survival and replication, ultimately leading to disease onset. However, few studies have focused on inhibiting the replication process of SARS-CoV-2. In this paper, we present a novel method to inhibit SARS-CoV-2 replication. Our method reconstructs network models of the host cell metabolic systems altered by virus invasion and predicts candidate antiviral targets via metabolic differential analysis. We separately analyzed gene expression data from lung and non-lung host cells to perform target prediction. The results indicate that D-alanine is a key metabolite affecting SARS-CoV-2 replication. Our approach is general and applicable to existing viruses, offering new ideas for dealing with viral diseases. Bioinformatics Computational Biology Systems Biology COVID-19 SARS-CoV-2 metabolic differences Full Text Supplementary Files STABLE1.xlsx List of genes related to Protein S. STABLE2.xlsx Results of single knockout S-associated gene experiments. STABLE3.xlsx Sample distribution of lung cell data. STABLE4.xlsx Details of non-lung cell samples. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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