A metabolic modeling approach reveals promising therapeutic targets and antiviral drugs to combat COVID-19

被引:0
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作者
Fernando Santos-Beneit
Vytautas Raškevičius
Vytenis A. Skeberdis
Sergio Bordel
机构
[1] Universidad de Valladolid,Institute of Sustainable Processes
[2] Lithuanian University of Health Sciences,Cell Culture Laboratory, Institute of Cardiology
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Scientific Reports | / 11卷
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摘要
In this study we have developed a method based on Flux Balance Analysis to identify human metabolic enzymes which can be targeted for therapeutic intervention against COVID-19. A literature search was carried out in order to identify suitable inhibitors of these enzymes, which were confirmed by docking calculations. In total, 10 targets and 12 bioactive molecules have been predicted. Among the most promising molecules we identified Triacsin C, which inhibits ACSL3, and which has been shown to be very effective against different viruses, including positive-sense single-stranded RNA viruses. Similarly, we also identified the drug Celgosivir, which has been successfully tested in cells infected with different types of viruses such as Dengue, Zika, Hepatitis C and Influenza. Finally, other drugs targeting enzymes of lipid metabolism, carbohydrate metabolism or protein palmitoylation (such as Propylthiouracil, 2-Bromopalmitate, Lipofermata, Tunicamycin, Benzyl Isothiocyanate, Tipifarnib and Lonafarnib) are also proposed.
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