Casticin for COVID-19

This review highlights Artemisia annua, a medicinal plant which grows in the Kingdom of Saudi Arabia, known for its abundant therapeutic properties. A. annua serves as a rich source of various bioactive compounds, including sesquiterpenoid lactones, flavonoids, phenolic acids, and coumarins. Among these, artemisinin and its derivatives are most extensively studied due to their potent antimalarial properties. Extracts and isolates of A. annua have demonstrated a range of therapeutic effects, such as antioxidant, anticancer, anti-inflammatory, antimicrobial, antimalarial, and antiviral properties. Given its significant antiviral activity, A. annua could be investigated for the development of new nutraceutical bioactive compounds to combat SARS-CoV-2. Artificial Intelligence (AI) can assist in drug discovery by optimizing the selection of more effective and safer natural bioactives, including artemisinin. It can also predict potential clinical outcomes through in silico modeling of protein–ligand interactions. In silico studies have reported that artemisinin and its derivatives possess a strong ability to bind with the Lys353 and Lys31 hotspots of the SARS-CoV-2 spike protein, demonstrating their effective antiviral effects against COVID-19. This integrated approach may accelerate the identification of effective and safer natural antiviral agents against COVID-19.

Abstract Background In November 2019, the world faced a pandemic called SARS-CoV-2, which became a major threat to humans and continues to be. To overcome this, many plants were explored to find a cure. Methods Therefore, this research was planned to screen out the active constituents from Artemisia annua that can work against the viral main protease Mpro as this non-structural protein is responsible for the cleavage of replicating enzymes of the virus. Twenty-five biocompounds belonging to different classes namely alpha-pinene, beta-pinene, carvone, myrtenol, quinic acid, caffeic acid, quercetin, rutin, apigenin, chrysoplenetin, arteannunin b, artemisinin, scopoletin, scoparone, artemisinic acid, deoxyartemisnin, artemetin, casticin, sitogluside, beta-sitosterol, dihydroartemisinin, scopolin, artemether, artemotil, artesunate were selected. Virtual screening of these ligands was carried out against drug target Mpro by CB dock. Results Quercetin, rutin, casticin, chrysoplenetin, apigenin, artemetin, artesunate, sopolin and sito-gluside were found as hit compounds. Further, ADMET screening was conducted which represented Chrysoplenetin as a lead compound. Azithromycin was used as a standard drug. The interactions were studied by PyMol and visualized in LigPlot. Furthermore, the RMSD graph shows fluctuations at various points at the start of simulation in Top1 (Azithromycin) complex system due to structural changes in the helix-coil-helix and beta-turn-beta changes at specific points resulting in increased RMSD with a time frame of 50 ns. But this change remains stable after the extension of simulation time intervals till 100 ns. On other side, the Top2 complex system remains highly stable throughout the time scale. No such structural dynamics were observed bu the ligand attached to the active site residues binds strongly. Conclusion This study facilitates researchers to develop and discover more effective and specific therapeutic agents against SARS-CoV-2 and other viral infections. Finally, chrysoplenetin was identified as a more potent drug candidate to act against the viral main protease, which in the future can be helpful.