Abstract
Context
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.
Methods
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 100 ns. 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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Data will be made available on request.
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Acknowledgements
The authors express their gratitude to the Plant Biology and Plant Biotechnology Laboratory at Guru Nanak College and the Phytochemistry Laboratory in the Department of Botany at Periyar University, Salem, for providing research facilities.
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PP and EG were responsible for conceptualization, data curation, and writing the original draft. PP and PT contributed to writing, review, and editing, and they performed the molecular docking. DP and SYC were involved in reviewing the article and conducting MD analysis. All authors have reviewed the manuscript. Additionally, all authors have read and agreed to the published version of the manuscript.
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Gayathiri, E., Prakash, P., Selvam, K. et al. In silico elucidation for the identification of potential phytochemical against ACE-II inhibitors. J Mol Model 30, 78 (2024). https://doi.org/10.1007/s00894-024-05868-6
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DOI: https://doi.org/10.1007/s00894-024-05868-6