In Silico Insights into Amalaki: Computational Profiling of Drug-Like Potentials of Emblica officinalis

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Rajeshwari V Kamat, Asath Bharathy P, S Srivarshini, Vijaykumar S Kamat

Abstract

The study explores the drug-likeness of phytochemicals derived from Emblica officinalis (Amla), a medicinal herb that is frequently employed in Ayurvedic and Unani traditional treatment systems. Well-known for its anti-inflammatory, anti-cancer, hepatoprotective, and antioxidant qualities, E. officinalis contains numerous bioactive compounds like flavonoids, tannins, and glycosides. Utilizing computer-aided drug design (CADD) tools, this research aims to evaluate the potential of these phytochemicals as viable drug candidates based on their physicochemical properties. Fifty selected phytochemicals were analyzed using canonical SMILES obtained from the PubChem database. ChemDraw was used to create chemical structures, and the MolSoft web server was used to predict drug-likeness scores using Lipinski's Rule of Five as the main screening criterion. Molecular weight (<500 Da), lipophilicity (ClogP <5), hydrogen bond donors (<5), and hydrogen bond acceptors (<10) are the criteria used by the rule to evaluate drug-likeness. Out of the 50 compounds evaluated, 30 met the drug-likeness criteria, showing promising profiles for oral bioavailability and therapeutic development. Nineteen compounds failed the criteria—five had two violations and fourteen had three violations—implying lower likelihood of oral activity. Tannic acid was excluded from the final analysis due to incomplete data from the software. The results demonstrate the efficacy of in silico tools in rapidly screening natural products for drug development. By merging traditional knowledge with modern computational approaches, this research underlines the potential of E. officinalis as a rich source of novel bioactive compounds. It is advised that more experiments be conducted to validate these results and get particular phytochemicals closer to medicinal uses. This study contributes to natural product-based drug discovery by identifying candidates suitable for further pharmacological development.

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