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The COVID-19 pandemic causing acute respiratory syndrome is a significant public health problem. Drugs that can treat this disease are currently a high priority. The SARS-CoV-2 spike protein and human ACE2 enzyme receptor, which both play important roles in virus entry into the host cell, are promising therapeutic targets for inhibiting viral infection. This research evaluates the potential of chalcone compounds to inhibit the spike proteins and ACE2 enzymes through molecular docking in silico approaches. Based on the ChemFaces database, we collected 92 chalcone compounds. These compounds were further docked to target the active sites of spike protein and human ACE2. After comparing the binding energies of the 92 compounds to artemisinin, ribavirin, and lopinavir, which have inhibitory activity to these protein targets of SARS-CoV-2, we chose 20 out of the 92 compounds that had a higher ability to inhibit the protein targets than the reference inhibitors. Next, five phytochemical compounds with the best binding energy were selected, which included flavanomarein, sarcandrone B, sarcandrone A, calyxin H, and sieboldin. Then, Lipinski’s 5 rule was used to evaluate the druglike properties of these compounds. Predictive ADME/tox filtering tests were also applied to the top docked compounds. The results suggest that sarcandrone B has good pharmacokinetic properties, which should be further explored as an anti-SARS-CoV-2. To confirm these findings, experimental studies are recommended.

Objectives: the COVID-19 pandemic triggering acute respiratory syndrome has become a major global health concern. After one year into this pandemic, special therapies for COVID-19 remain an unprecedented challenge to mankind and finding drugs to treat this disease is extremely urgent. The SARS-CoV-2 RNAdependent RNA polymerase (RdRp) enzyme that regulates viral replication has been examined as a potential therapeutic target for the inhibition of SARS-CoV-2 infection. In this study, the authors evaluated the ability of RNA-dependent RNA polymerase drug inhibitors by using an in silico molecular docking model. Methods: the 3D structure of RdRp enzyme (PDB ID:6M71, resolution of 2.90 Å) was derived from the Protein Data Bank RCSB. The ligand structures were collected from DrugBank for the RdRp target. Molecular docking was done by AutoDock Vina software. Lipinski’s rule of five is used to compare compounds with drug-like and nondrug-like properties. Pharmacokinetic parameters of potential compounds were evaluated using the pkCSM tool. Results: based on the DrugBank database, we collected 192 antiviral molecules and compared them to remdesivir, which has inhibitory activity with this protein target. Results showed that 26 out of 192 compounds have a higher ability to inhibit the SARS-CoV-2 RdRp enzyme than remdesivir. Next, 6 drugs were selected by visually inspecting the docking results with focus on the main interaction between crucial residues at the binding site of the SARS-CoV-2 RdRp enzyme. For the visual inspection, the existence of polar interactions with ASP760 and ASP761 were utilised as the preference criterion. Finally, Lipinski’s rule of 5 criteria and absorption, distribution, metabolism, excretion and toxicity (ADMET) profile analysis suggested five drugs that have good pharmacokinetic properties. Conclusions: these drugs were dihydroergotamine, sofosbuvir, nilotinib, tipranavir, and darunavir and may be used as anti-SARS-CoV-2 agents.