Youn_2024_Int.J.Mol.Sci_25_

Reference

Title : Determination of Potential Lead Compound from Magnolia officinalis for Alzheimer's Disease through Pharmacokinetic Prediction, Molecular Docking, Dynamic Simulation, and Experimental Validation - Youn_2024_Int.J.Mol.Sci_25_
Author(s) : Youn K , Jun M
Ref : Int J Mol Sci , 25 : , 2024
Abstract :

Amyloid beta protein (Abeta) deposition has been implicated as the molecular driver of Alzheimer's disease (AD) progression. The modulation of the formation of abnormal aggregates and their post-translational modification is strongly suggested as the most effective approach to anti-AD. Beta-site APP-cleaving enzyme 1 (BACE1) acts upstream in amyloidogenic processing to generate Abeta, which rapidly aggregates alone or in combination with acetylcholinesterase (AChE) to form fibrils. Accumulated Abeta promotes BACE1 activation via glycogen synthase kinase-3beta (GSK-3beta) and is post-translationally modified by glutaminyl cyclase (QC), resulting in increased neurotoxicity. A novel multi-target inhibitor as a potential AD agent was identified using an in silico approach and experimental validation. Magnolia officinalis, which showed the best anti-AD activity in our preliminary study, was subjected to analysis, and 82 compounds were studied. Among 23 compounds with drug-likeness, blood-brain barrier penetration, and safety, honokiol emerged as a lead structure for the inhibition of BACE1, AChE, QC, and GSK-3beta in docking and molecular dynamics (MD) simulations. Furthermore, honokiol was found to be an excellent multi-target inhibitor of these enzymes with an IC(50) of 6-90 microM, even when compared to other natural single-target inhibitors. Taken together, the present study is the first to demonstrate that honokiol acts as a multiple enzyme inhibitor with an excellent pharmacokinetic and safety profile which may provide inhibitory effects in broad-range areas including the overproduction, aggregation, and post-translational modification of Abeta. It also provides insight into novel structural features for the design and discovery of multi-target inhibitors for anti-AD.

PubMedSearch : Youn_2024_Int.J.Mol.Sci_25_
PubMedID: 39408835

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Citations formats

Youn K, Jun M (2024)
Determination of Potential Lead Compound from Magnolia officinalis for Alzheimer's Disease through Pharmacokinetic Prediction, Molecular Docking, Dynamic Simulation, and Experimental Validation
Int J Mol Sci 25 :

Youn K, Jun M (2024)
Int J Mol Sci 25 :