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10.12688/f1000research.26731.1

http://scihub22266oqcxt.onion/10.12688/f1000research.26731.1
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33145015!7590895!33145015
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suck abstract from ncbi


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pmid33145015      F1000Res 2020 ; 9 (ä): 1203
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  • Bioinformatic study to discover natural molecules with activity against COVID-19 #MMPMID33145015
  • Singh S; Florez H
  • F1000Res 2020[]; 9 (ä): 1203 PMID33145015show ga
  • Background: In 2020, the world has struggled to deal with coronavirus disease 2019 (COVID-19), which started in 2019 in China and has spread throughout the globe, affecting at least 31,175,835 humans globally and claiming 962,634 lives reported till 22nd September, 2020 by the World Health Organization. The main causative agent for this disease is known as severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). So far, there is no cure or proven therapeutics available till date. Therefore, we undertook this study to fi nd the most probable drug candidate through a bioinformatics study. Methods: Thus, we virtually screened the Zinc natural database using HTVS tool through molecular docking studies to analyze molecules recommended for the treatment of COVID-19. Results: Ramipril benzyl ester, propafenone dimer and Lariciresinol are three important drugs found from the present study due to their medicinal application which could be helpful in treating the disease. Stylopine, quillaic acid, cinobufagin, vitisinol C, segetalin A, scopolamine, 3-oxo glycyrrhetinic acid, conchinone B, lactimidomycin and cardinalins 4 are the other lead molecules that could be used as therapeutics against COVID-19 disease. Conclusions: The studied molecules could act as an effective inhibitory drug against COVID-19.
  • |*Computational Biology[MESH]
  • |*Drug Discovery[MESH]
  • |Antiviral Agents/*chemistry[MESH]
  • |Betacoronavirus/*drug effects[MESH]
  • |COVID-19[MESH]
  • |China[MESH]
  • |Coronavirus Infections/drug therapy[MESH]
  • |Humans[MESH]
  • |Molecular Docking Simulation[MESH]
  • |Pandemics[MESH]
  • |Pneumonia, Viral/drug therapy[MESH]


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