In silico molecular docking and molecular dynamic simulation of agarwood compounds with molecular targets of Alzheimer's disease .

Abstract

Background: Alzheimer's disease (AD) is a neurological condition that primarily affects older people. Currently available AD drugs are associated with side effects and there is a need to develop natural drugs from plants. Aquilaria is as an endangered medicinal plant genus (commonly called agarwood plants) and various products of Aquilaria plant spp. including resinous heartwood, leaves, bark, and stem have been widely used in various traditional medicine systems. Research on agarwood plants is sparse and only a few previous studies demonstrated their neuroprotective properties in vitro. Owing to the presence of a plethora of secondary metabolites in agarwood plants, it is imperative not only to protect these plants but also evaluate the bioactivity of agarwood phytochemicals.

Methods: This study used Molsoft tools to predict the physicochemical properties of agarwood ligands, including the number of H-bond donors and acceptors, polar surface area, lipophilicity, solubility, and the molecular polar surface area and volume of agarwood ligands. Additionally, ADMET (absorption, digestion, metabolism, excretion, and toxicity) properties were predicted using ADMETlab 2.0. Computational methods such as AutoDock Vina and molecular dynamic (MD) simulations were employed for the docking of 41 selected agarwood compounds with AD-related molecular targets.

Results and conclusion: According to docking data, three compounds aquilarisin (ASN), aquilarisinin (ANN), aquilarixanthone (AXN) showed highest binding affinity to selected AD targets compared to their known inhibitors. MD simulation studies revealed that, selected agarwood compounds' protein-ligand complexes showed remarkable structural stability throughout 100ns simulation. The agarwood chemicals aquilarisin, aquilarisinin, aquilarixanthone, pillion (PLN), and agarotetrol (AGT) are consequently suggested as some of the found hits against AD targets, however, additional experimental validation is required to establish their effectiveness.