Abstract
AbstractRosa laevigata Michx., a member of the Rosaceae family, is a famous traditional Chinese medicine and edible food in Asian countries. The major active ingredient is triterpenoid, which has anti‐Alzheimer's Disease (AD), antioxidant and neuroprotection properties. However, the properties of “multi‐component structure” and “multi‐directional target” make it impossible to explain the molecular mechanism by conventional ways. The present study aimed to predict the multi‐target mechanisms of triterpenoids in R. laevigata against AD using high performance liquid chromatography equipped with quadrupole time‐of‐flight mass spectrometer (HPLC‐Q‐TOF MS) approach, network pharmacology analysis, dynamics simulation (MDs) and validation of the predicted results with straight‐target tests as well as neuroprotection model. Firstly, bioassay‐guided fractionation of R. laevigata integrated with LC‐MS/MS analysis of the most prospective enriched fractions in terms of anti‐AD efficacy was commenced. Subsequently, multi‐level network model of “multi components‐multi‐targets‐multiple pathways” was established based on the identification of 69 triterpenoids. Complementarily, 64 AD‐related targets were identified through various databases. Network structure analysis illuminated that the intricate pharmacological mechanisms improving cognitive dysfunction of AD was superiorly combined with the crucial targets of APP, APOE, VEGFA, IL1B, MAPT, PSEN1 and BACE and further regulation of principal pathways as HIF‐1 and Calcium signaling pathways. In addition, AChE, BChE and BACE inhibitory activities in vitro showed that nine compounds exhibited potential inhibitory activities. The neuroprotective effects also had a similar effect on H2O2‐induced SH‐SY5Y cell injury. The results show that R. laevigata and its bioactive triterpenoids can pave the way for potential application as inhibitors for treatment of AD.
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