Structural and dynamical analysis of an integrated human/virus metabolic model provides insight into new treatment strategies against Covid-19
Bridget P. Bannerman, Jorge Júlvez, Alexandru Oarga, Tom L. Blundell, Pablo A Moreno, R. Andrés Floto · 2021
The coronavirus disease 2019 (COVID-19) pandemic outbreak caused by the new coronavirus (SARS-CoV-2) is currently responsible for over 351 thousand deaths in 217 countries across the world (https://www.who.int/emergencies/diseases/novel-coronavirus-2019). The absence of FDA approved drugs against the new SARS-CoV-2 virus has prompted the urgent need to design new drugs and treatment management strategies against COVID-19. We provide a combination of structural and dynamic modelling approaches to predict new drug targets against the SARS-CoV-2 virus and to determine drug optimisation strategies. This methodology involves the analysis of a stoichiometric metabolic model that integrates cell metabolism in humans with the SARS-CoV-2 virus. We also compared the interactions that occur between the Angiotensin-converting enzyme 2 (ACE2), the cellular receptor for the 2002 SARS-CoV virus, the new coronavirus (SARS-CoV-2) and associated cofactors. The model has provided an in-silico comparison of the biochemical demands of the viruses versus the host cells and predicted 18 essential reactions as drug targets from an integrated human cell and SARS-CoV-2 virus system. We are expanding the model to predict the effect of various treatment regimens to ensure maximum drug optimisation strategies against the virus.