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Original Article

J App Pharm Sci. 2023; 13(4): 157-167


Pharmacophore-based virtual screening & molecular docking studies on selected plant constituents of Plantago major

Muni Sireesha Sunkara, Vinutha Kuchana, Jahnavi Pragna Sree, Rachana Prabugari, Ashwini Pilli, Farhani Irum, Saritha Jyostna Tangeda, Dipankar Bhowmik.




Abstract
Cited by 1 Articles

Phytochemicals are a striking source to discover new leads for the expansion of novel compounds for several diseases. In this study, various in silico techniques are used to showcase the multitarget inhibitors of selected plant constituents of Plantago major. Five plant components having an anti-inflammatory activity are used to build a pharmacophore model with “PharmaGist webserver” which generated a four-point hypothesis. The best model with a score of 12.402, was used to screen the National Cancer Institute database of the Pharmit web server to obtain similar pharmacophore hits. Subsequently, molecular docking was performed on the Cyclooxygenase-2 (PDB ID: 4COX) protein by using Autodock Vina, to prioritize top lead molecules. Among all the hits, four compounds have the best dock scores than the standard Celecoxib (−9 kcal/mol). From our result, compound NSC86473 has the highest potential as an anti-inflammatory agent with binding energy (−10 kcal/mol) and may act as a powerful inhibitor against Cyclooxygenase 2 as it has the lowest binding energy than the standard with specified pharmacophoric features according to developed pharmacophore model 1 model. In accordance with earlier findings, it can provide a few insights to research scholars in the future to identify and design new lead molecules with effective anti-inflammatory activity.

Key words: Autodock Vina, Molecular Docking, Pharmacophore modeling, PharmaGist, Pharmit, Virtual Screening.






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