Abstract

The present study aims to investigate the therapeutic potential of phytocompounds derived from Annona reticulata leaves for the treatment of hypertension, utilizing computational methodologies. Gaining a comprehensive understanding of the molecular interactions between neophytadiene and γ-sitosterol holds significant importance in the advancement of innovative therapeutic approaches. This study aims to examine the inhibitory effects of neophytadiene and γ-sitosterol using molecular docking and dynamics simulations. Additionally, we will evaluate their stability and predict their drug-like properties as well as their ADME/toxicity profiles. Neophytadiene and γ-sitosterol have a substantial binding affinity with 1O8A, as shown by the docking study. The stability of the complexes was confirmed through molecular dynamics simulations, while distinct clusters were identified using PCA. These findings suggest the presence of potential stabilizers. The drug-likeness and ADME/toxicity predictions revealed positive characteristics, such as efficient absorption rates, limited distribution volume and non-hazardous profiles. The neophytadiene and γ-sitosterol exhibit potential as hypertension medication options. Computational investigations reveal that these compounds exhibit high affinity for binding, stability and favourable pharmacokinetic properties. The results of this study lay the groundwork for additional experimental verification and highlight the promising prospects of utilizing natural compounds in the field of pharmaceutical research. Target proteins (1O8A) were used to perform molecular docking with representative molecules. Stability, conformational changes and binding energies were assessed through molecular dynamics simulations lasting 100ns. Principal component analysis (PCA) was utilized to analyze molecular dynamics (MD) simulation data, to identify potential compounds that could stabilize the main protease. The safety and pharmacokinetic profiles of the compounds were evaluated through drug-likeness and ADME/toxicity predictions.

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