000119596 001__ 119596
000119596 005__ 20230519145540.0
000119596 0247_ $$2doi$$a10.26508/LSA.202000954
000119596 0248_ $$2sideral$$a127039
000119596 037__ $$aART-2021-127039
000119596 041__ $$aeng
000119596 100__ $$aBannerman B.P.
000119596 245__ $$aIntegrated human/SARS-CoV-2 metabolic models present novel treatment strategies against COVID-19
000119596 260__ $$c2021
000119596 5060_ $$aAccess copy available to the general public$$fUnrestricted
000119596 5203_ $$aThe coronavirus disease 2019 (COVID-19) pandemic caused by the new coronavirus (SARS-CoV-2) is currently responsible for more than 3 million deaths in 219 countries across the world and with more than 140 million cases. The absence of FDA-approved drugs against SARS-CoV-2 has highlighted an urgent need to design new drugs. We developed an integrated model of the human cell and SARS-CoV-2 to provide insight into the virus'' pathogenic mechanism and support current therapeutic strategies. We show the biochemical reactions required for the growth and general maintenance of the human cell, first, in its healthy state. We then demonstrate how the entry of SARS-CoV-2 into the human cell causes biochemical and structural changes, leading to a change of cell functions or cell death. A new computational method that predicts 20 unique reactions as drug targets from our models and provides a platform for future studies on viral entry inhibition, immune regulation, and drug optimisation strategies. The model is available in BioModels (https://www.ebi.ac.uk/biomodels/MODEL2007210001) and the software tool, findCPcli, that implements the computational method is available at https://github.com/findCP/findCPcli. © 2021 Bannerman et al.
000119596 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000119596 590__ $$a5.781$$b2021
000119596 591__ $$aBIOLOGY$$b17 / 94 = 0.181$$c2021$$dQ1$$eT1
000119596 592__ $$a2.318$$b2021
000119596 593__ $$aBiochemistry, Genetics and Molecular Biology (miscellaneous)$$c2021$$dQ1
000119596 593__ $$aPlant Science$$c2021$$dQ1
000119596 593__ $$aEcology$$c2021$$dQ1
000119596 594__ $$a6.5$$b2021
000119596 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000119596 700__ $$0(orcid)0000-0002-7093-228X$$aJúlvez J.$$uUniversidad de Zaragoza
000119596 700__ $$aOarga A.
000119596 700__ $$aBlundell T.L.
000119596 700__ $$aMoreno P.
000119596 700__ $$aFloto R.A.
000119596 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000119596 773__ $$g4, 10 (2021), e202000954 [13p]$$pLife sci. alliance$$tLife Science Alliance$$x2575-1077
000119596 8564_ $$s2582865$$uhttps://zaguan.unizar.es/record/119596/files/texto_completo.pdf$$yVersión publicada
000119596 8564_ $$s3160791$$uhttps://zaguan.unizar.es/record/119596/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000119596 909CO $$ooai:zaguan.unizar.es:119596$$particulos$$pdriver
000119596 951__ $$a2023-05-18-15:40:16
000119596 980__ $$aARTICLE