PropertyValue
?:abstract
  • Background: The dawn of the year 2020 witnessed the spread of the highly infectious and communicable disease coronavirus disease 2019 (COVID-19) globally since it was first reported in 2019. Severe acute respiratory syndrome coronavirus-2 is the main causative agent. In total, 3,096,626 cases and 217,896 deaths owing to COVID-19 were reported by 30th April, 2020 by the World Health Organization. This means infection and deaths show an exponential growth globally. In order to tackle this pandemic, it is necessary to find possible easily accessible therapeutic agents till an effective vaccine is developed. Methods: In this study, we present the results of molecular docking processes through high throughput virtual screening to analyze drugs recommended for the treatment of COVID-19. Results: Atovaquone, fexofenadine acetate (Allegra), ethamidindole, baicalin, glycyrrhetic acid, justicidin D, euphol, and curine are few of the lead molecules found after docking 129 known antivirals, antimalarial, antiparasitic drugs and 992 natural products. Conclusions: These molecules could act as an effective inhibitory drug against COVID-19.
?:creator
?:journal
  • F1000Res
?:license
  • unk
?:publication_isRelatedTo_Disease
?:source
  • WHO
?:title
  • Coronavirus disease 2019 drug discovery through molecular docking
?:type
?:who_covidence_id
  • #676729
?:year
  • 2020

Metadata

Anon_0  
<http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://purl.org/net/provenance/ns#DataItem>
<http://www.w3.org/1999/02/22-rdf-syntax-ns#type> <http://www.w3.org/2004/03/trix/rdfg-1/Graph>
<http://xmlns.com/foaf/0.1/primaryTopic> <https://research.tib.eu/covid-19/entity/udowk0iw>
<http://xmlns.com/foaf/0.1/topic> Anon_0
<http://www.ontologydesignpatterns.org/cp/owl/informationrealization.owl#realizes> <https://research.tib.eu/covid-19/data/entity/udowk0iw>
<http://purl.org/net/provenance/ns#createdBy>
Anon_1   (more)
expand all