Quantitative ethnobotanical study in Gafargaon Sub-district and unveiling drug candidates through molecular docking and dynamics simulation approaches
DOI:
https://doi.org/10.3329/bjpt.v30i1.67044Keywords:
Ethnobotany; Informant consensus factor; Fidelity; Molecular docking; Molecular dynamics simulation; Rheumatoid arthritis; JAK1.Abstract
An ethnobotanical investigation was carried out in Gafargaon sub-district (upazila) under Mymensingh district, Bangladesh that unveiled a total of 79 medicinal plant species under 74 genera and 46 families which were used to treat various ailments through 106 formularies. In addition, molecular docking and dynamics simulation studies were performed based on ethnobotanical outcome for the first time in Bangladesh to unveil potential drug candidates. The study revealed that most of the species used for primary healthcare were herbs (44.3%) followed by trees (36.7%), shrubs (10.2%) and climbers (8.8%). Leaves were found to be the most frequently used part (34%) compared to other plant parts. Factor of informant consensus values ranged from 0.975 to 0.984 and the highest value was recorded for respiratory tract disorders (0.984). Maximum number of taxa was unraveled to treat digestive and gastrointestinal disorders. Fidelity level varied from 41.2 to 100%, where 11 species showed 100% fidelity, and the citation frequency was found above 70% for 15 different ailments. Molecular docking study exposed 60% Stephania japonica phytocompounds scoring higher than the control drug Ibuprofen (-7.0 kcal/mol) targeting rheumatoid arthritis. The phytocompounds Oxostephanine, Trilobine and Epistephanine were identified as lead drug candidates with binding affinity of -9.7, -8.7 and -8.6 kcal/mol, respectively. Molecular interactions of these compounds were found significant to identify potential drug surface hotspots. Molecular dynamics simulation shed light on regional flexibility profiles and unraveled notable structural stability of the top three phytocompounds. The present study would offer foundational data for identifying potential bioactive compounds that could be utilized in novel drug discovery efforts.
Bangladesh J. Plant Taxon. 30(1): 53-76, 2023 (June)
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