6533b838fe1ef96bd12a47e9
RESEARCH PRODUCT
Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning.
Mohamed E.m. SaeedOnat KadiogluHenry Johannes GretenThomas A. Efferthsubject
0301 basic medicineSimeprevirArtificial intelligencevirusesMERS Middle East Respiratory SyndromeHealth InformaticsBiologyMachine learningcomputer.software_genremedicine.disease_causeAntiviral AgentsArticleWHO World Health OrganizationAUC area under the curve03 medical and health sciences0302 clinical medicinessRNA single-stranded RNA virusmedicineChemotherapyHumansSARS severe acute respiratory syndromeCOVID-19 coronavirus disease 2019CoronavirusNatural productsVirtual screeningACE2 angiotensin converting enzyme 2Drug discoverybusiness.industrySARS-CoV-2COVID-19LBE lowest binding energyFDA Food and Drug AdministrationROC receiver operating characteristicComputer Science ApplicationsHIV human immunodeficiency virusMolecular Docking SimulationDrug repositioning030104 developmental biologyDrug developmentSevere acute respiratory syndrome-related coronavirusParitaprevirInfectious diseasesRespiratory virusArtificial intelligenceSupervised Machine Learningbusinesscomputer030217 neurology & neurosurgerydescription
Coronavirus disease 2019 (COVID-19) is a major threat worldwide due to its fast spreading. As yet, there are no established drugs available. Speeding up drug discovery is urgently required. We applied a workflow of combined in silico methods (virtual drug screening, molecular docking and supervised machine learning algorithms) to identify novel drug candidates against COVID-19. We constructed chemical libraries consisting of FDA-approved drugs for drug repositioning and of natural compound datasets from literature mining and the ZINC database to select compounds interacting with SARS-CoV-2 target proteins (spike protein, nucleocapsid protein, and 2′-o-ribose methyltransferase). Supported by the supercomputer MOGON, candidate compounds were predicted as presumable SARS-CoV-2 inhibitors. Interestingly, several approved drugs against hepatitis C virus (HCV), another enveloped (−) ssRNA virus (paritaprevir, simeprevir and velpatasvir) as well as drugs against transmissible diseases, against cancer, or other diseases were identified as candidates against SARS-CoV-2. This result is supported by reports that anti-HCV compounds are also active against Middle East Respiratory Virus Syndrome (MERS) coronavirus. The candidate compounds identified by us may help to speed up the drug development against SARS-CoV-2.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2021-03-01 | Computers in biology and medicine |