Vol. 8, Issue 8 (2019)
Leaf phytoligands of Annona reticulata Linn.: molecular docking approach against proinflammatory receptors to detect antiinflammatory small molecules
Bhaskar Karmakar, Ipsita Ghosh, Partha Talukdar and Soumendra Nath Talapatra
Annona reticulata Linn. is well-known medicinal tree and contains phytochemicals to prevent several diseases through traditional knowledge. The aim of the present in silico study was to predict the binding affinity and energy of common phytochemicals especially saponins of A. reticulata compared to synthetic drugs (Ibuprofen and Indomethacin) on three proinflammatory receptors viz. tumour necrosis factor-α (TNF-α) and interleukins (IL-1β and IL-6) through molecular docking and interaction. The structure-based virtual screening was done by using PyRx tool (Version 0.8) to detect receptor-ligand binding affinity and energy. These receptors were obtained (PDB IDs: 2AZ5, 2NVH and 1P9M) from the European Protein Data Bank (ePDB) and the information on selected phytoligands (saponins) of A. reticulata and two synthetic ligands were obtained from PubChem database. Present molecular docking indicated that favourable binding energy was observed in Farnesyl acetate-(E,E) (-9.7 Kcal/mol) followed by Furostan and Taraxerol (-9.6 Kcal/mol) on TNF-α receptor while Kaurenoic acid (-7.2 Kcal/mol) on IL-1β receptor and Taraxerol and Furostan (-9.4 and -8.9 Kcal/mol) on IL6 receptor when compared to Indomethacin (-7.6, -6.7 and -7.5 Kcal/mol) and Ibuprofen (-6.7, -5.7 and -6.1 Kcal/mol) for these three receptors. This is a computational prediction to identify lead compound(s) for anti-inflammatory agents, which may substitute as a cost-effective natural product to prevent pain and inflammation. Future experimental assay with these natural products is suggested to validate the present predictive results.
How to cite this article:
Bhaskar Karmakar, Ipsita Ghosh, Partha Talukdar and Soumendra Nath Talapatra. Leaf phytoligands of <em>Annona reticulata </em>Linn.: molecular docking approach against proinflammatory receptors to detect antiinflammatory small molecules. 2019; 8(8): 32-39.