In silico ADMET Study, Molecular Docking and Dynamic Simulation of Tuber Extract of Amorphophallus paeoniifolius for Anti-inflammatory Target Prediction in Asthma

PurposeA significant disease impacting quality of life is asthma, a pulmonary condition. Amorphophallus paeoniifolius (Donnst) Nicolson, traditionally used for allergic asthma belonging to Araceae family, shows therapeutic potential against inflammation. Till today scientific validation of this plant specifically molecular mechanisms against asthma remains incomplete.MethodsThis study aimed to elucidate the molecular mechanisms of compounds present in A. paeoniifolius against asthma using a protein-target approach. Molecular docking assessed seven compounds (beta-sitosterol, betulinic acid, gallic acid, lupeol, quercetin, resveratrol, stigmasterol) of A. paeoniifolius against targets 4QTB and 2AZ5 using AutoDock 4.2 and Maestro for simulation. Molecular dynamics (MD) simulations were analyzed for 200 ns for stability and interactions of compounds relevant to allergic asthma. In-silico ADMET predictions indicated favourable absorption and drug-like properties of compounds.ResultsDocking analysis revealed that betulinic acid and lupeol (compounds 2 and 4) showed strong binding - 11.2 and - 10.82 towards selected target 4QTB whereas - 9.80 and - 7.26 towards 2AZ5 suggesting their stability towards proteins to prevent inflammatory pathway activation. MD simulations supported these findings, showing stable interactions between protein and ligands for 200 ns. This study suggests A. paeoniifolius could be beneficial in allergic asthma management through its active compounds.ConclusionThe findings provide a way for exploring multi-phytoanalytes and novel therapeutic regimen in treatment of allergic asthma. Insights from ADMET predictions, molecular docking, and MD simulations offer a foundation for developing new anti-inflammatory drugs derived from A. paeoniifolius tuber extract.