Background: in the twenty-first century, the emergence of COVID-19 as a highly transmissible pandemic disease caused by SARS-CoV-2 posed a significant threat to humanity. Aims & Objectives: the disease spreads through small respiratory droplets, necessitating the use of various compounds for treatment, with alkaloids being recognized as particularly crucial owing to their diverse pharmaceutical properties. Methodology: in this study, a dataset comprising 100 natural alkaloids obtained from the literature was transformed into 2D chemical structures using Chem Draw 19.1. Subsequently, 3DQSAR studies were conducted on the dataset, resulting in the automatic screening of 50 compounds from the initial pool of 100 compounds. The values of q 2 and r 2 of the validated field-based 3DQSAR model were 0.7186 and 0.971, respectively. The validated atom-based 3DQSAR model has q 2 and r 2 scores of 0.6025 and 0.9845, respectively. Based on the obtained results, 10 compounds with exceptionally active predictive IC50 values were selected for further analysis. Docking experiments were then performed on the selected compounds, and the top three compounds with the highest docking scores were identified as diazepinomicin, (+)-N-methylisococlaurine, and hymenocardine-H. After docking, MM-GBSA was performed on the complexes of diazepinomicin, (+)-N-methylisococlaurine and hymenocardine-H with their corresponding proteins, which resulted in the authentication of the molecular docking scores. MD simulations were also performed to check the flexibility, stability and compactness of these complexes for revalidation of docking scores. Results: finally, ADMET experiments revealed that (+)-N-methylisococlaurine exhibited the most favourable properties among these three compounds.
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