ABSTRACT
Context: The outbreak of a novel coronavirus, SARS-CoV-2 has caused an unprecedented COVID-19 pandemic. To put an end to this pandemic, effective antivirals should be identified or developed for COVID-19 treatment. However, specific and effective antivirals or inhibitors against SARS-CoV-2 are still lacking. Aim(s): To evaluate bioactive compounds from Phyllanthus tenellus and Kaempferia parviflora as inhibitors against two essential SARS-CoV-2 proteins, main protease (Mpro) and RNA-dependent RNA polymerase (RdRp), through molecular docking studies and to predict the drug-likeness properties of the compounds. Method(s): The inhibition potential and interaction of P. tenellus and K. parviflora compounds against Mpro and RdRp were assessed through molecular docking. The drug-likeness properties of the compounds were predicted using SwissADME and AdmetSAR tools. Result(s): Rutin and ellagic acid glucoside from P. tenellus and 4-hydroxy-6-methoxyflavone and 5-hydroxy-3,7,4'-trimethoxyflavone from K. parviflora exhibited the highest binding conformations to Mpro by interacting with its substrate binding site that was predicted to halt the Mpro activity. As for RdRp, ellagitannin and rutin from P. tenellus and peonidin and 5,3'-dihydroxy-3,7,4'-trimethoxyflavone from K. parviflora were the best-docked compounds that bound to the RdRp catalytic domain (Asp760 and Asp761) and NTP-entry channel that were anticipated to stop RNA polymerization. However, in the context of drug developability, 4-hydroxy-6-methoxyflavone, 5-hydroxy-3,7,4'-trimethoxyflavone, peonidin and 5,3'-dihydroxy-3,7,4'-trimethoxyflavone from K. parviflora were highly potential to be oral active drugs compared to rutin, ellagic acid glucoside and ellagitannin from P. tenellus. Conclusion(s): P. tenellus and K. parviflora compounds, particularly the aforementioned compounds, were suggested as potential inhibitors of SARS-CoV-2 Mpro and RdRp. Copyright © 2022 Journal of Pharmacy & Pharmacognosy Research.
ABSTRACT
The purpose of this paper is to predict the final size of the COVID-19 in West Java Province, Indonesia. This paper describes the mathematical modeling and dynamics of a COVID-19 by using the SIR epidemic model. To predict the final size of the positive cases of COVID-19 that occur, the minimum function of the final number of susceptible and recovered is performed. The numerical simulation was performed with data after West Java Government implemented Large-Scale Social Restrictions. Based on the numerical results is founded the final size of the COVID-19 in West Java Province is 22743 people. This number might have been greater if the Government did not carry out Large-Scale Social Restrictions.