In-vitro and in-silico therapeutic investigation and biochemical characterization of Mangifera indica: A flowering plant

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Background: Mangifera indica L. Known as the mango, is a type of flowering plant in the Anacardiaceae family that has been grown for thousands of years in India. Mango fruit is a source of fiber, essential amino acids and number of vitamins and other phytochemicals. Traditional medicine systems have widely used different parts of mango plant as a preventive measure to treat several diseases. The various bioactive phytochemicals present in the M. indica contributes to its anti-inflammatory and health promoting properties. Aim and Objectives: Our present research work aims at the comparative phytochemical analyses along with in-vitro and in-silico pharmacological screening of three different cultivars of mango leaves (Himsagar, Langra, Amrapali) via molecular docking interactions as well as physicochemical characterizations of prepared metal nanoconjugates. Results: The results highlighted that ethanolic extract of Amrapali showed maximum total polyphenol (138.75±3.38 mg GAE/ gm. of DW) and flavonoid (52.23±7.41 mg QE/ gm. of DW) content, while ethanolic Himsagar extract showed maximum total flavonol (13.91±0.38 mg QE/ gm. of DW) and tannin (7.16±0.05 mg TAE/ gm. of DW) content. On the contrary, ethanolic extract of Amrapali showed highest% of in-vitro free radical scavenging potential. In-silico evaluation of medicinal potential of the extracts showed that eremophyllene and β-bisabolene showed the showed highest binding affinity (-7.3 kcal/mol.) against Humna androgen receptor (PDB ID: 1E3G), comparable to standard anticancer drug tamoxifen (-7.4 kcal/mol.). The result of the antibacterial study of these nano-conjugates showed antibacterial activity against both Escherichia coli and Staphylococcus aureus. Conclusion: The overall research study showed that mango leaves contain several naturally occurring potential bioactive compounds that can act as a source of therapeutic possibility which is proven via both in-vitro and in-silico mode of characterizations.