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In Silico Docking, Drug-likeness and Toxicity Prediction Studies of Bioactive Compounds of Eurycoma longifolia as Potential Multi-targeted Antiviral Agents against SARS-CoV-2

2024/12/24 by Veerasamy, Ravichandran, Seenivasa, Raghuraman, Thangavelu, Prabha +2
#COVID-19 #Eurycoma longifolia #SARS-CoV-2 #Tongkat Ali #drug−likeness profiles #molecular docking #pharmacokinetics

paper · doi:10.48317/imist.prsm/morjchem-v13i1.45142

Abstract

The recent pandemic infection COVID-19 by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused high mortality in the last two and a half years. Even though vaccines available for COVID-19 prevention, till today, no effective drug is available for this deadly virus disease. But there are many reports on natural and synthetic products with action against SARS-CoV-2. This in-silico study tries to discover a novel potential inhibitor to the target enzymes of the SARS-CoV-2, such as main protease (Mpro, PDB: 6LU7), papain like protease (PLpro, PDB: 6WUU), and RNA-dependent RNA polymerase (RdRp, PDB: 6M71), from the bioactive compounds of Eurycoma longifolia by molecular docking. The pharmacokinetic and toxic profile of the compounds were also predicted by in-silico analysis. Among the 30 bioactive compounds of Eurycoma longifolia, the compounds melianone, pasakbumin B, eurycomanol, and niloticin showed a well binding affinity (kcal/mol) against SARS-CoV-2 target enzymes used in the study, and it may be considered an effective multi targeted COVID-19 inhibitor. Intriguingly one of the bioactive compounds melianone showed a well binding affinity of −8.1 kcal mol-1 for Mpro, -8.7 kcal mol-1 for PLPro, and -7.8 kcal mol-1 for RdRp. The lead molecule melianone was further analyzed by the detailed molecular dynamics study to establish the stability of ligand-enzyme complex. In-silico drug-likeness and toxicity prediction results are also provided promising arguments for further in vitro and in vivo studies to assess these compounds’ ability to compete with the SARSCoV-2.

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