Revisiting the COVID-19 Pandemic: A Comparative Analysis between Traditional and Synthetic Modes of Treatment with the Aid of In-silico Methods

Introduction/Background: The COVID-19 pandemic has severely disrupted global health systems, highlighting the urgent need for effective treatment strategies. This article aims to provide an assessment of the pandemic's current status and examines the effectiveness of traditional treatments against innovative synthetic approaches. Materials and Methods: The article explores synthetic strategies involving repurposed antiviral drugs, supportive care, and vaccinations. It emphasizes the role of computational modeling and artificial intelligence in engineering molecules with potent antiviral properties. In-silico methods were utilized to accelerate chemical library screenings, predict efficacy, and assess interactions between viral proteins and potential treatments. Results: Studies employing molecular docking analysis have evaluated the efficacy of approved antiviral drugs and natural compounds. Notably, Azithromycin was found to have a potential inhibitory effect with a binding energy of -9.69, while natural compounds like Camphor and Curcumin displayed binding energies of -5.18 and -6.16, respectively. Discussion: Synthetic treatments showed effectiveness in inhibiting viral proteins and facilitating rapid development, while natural products were more effective in preventing virus entry. Conclusion: Based on in-silico docking studies, it can be concluded that natural products have more therapeutic effects than synthetic drugs.