Identification and extraction of bioactive constituents from Gardenia jasminoides Ellis: Evaluation of their acetylcholinesterase inhibitory potential

Abstract

Research in functional foods faces two major challenges due to the complexity of natural food components: accurate and rapid identification of bioactive compounds, and their precise extraction. To address these challenges, this study developed an integrated strategy to identify and isolate acetylcholinesterase inhibitors (AChEIs) from Gardenia jasminoides Ellis (GJE)—a plant with both medicinal and edible value—while evaluating their potential against Alzheimer’s disease (AD). First, affinity ultrafiltration-liquid chromatography-mass spectrometry (AUF-LC-MS) (a technique that uses AChE as a target to specifically capture binding compounds from complex extracts) was employed to screen candidate AChEIs from GJE. To verify the anti-dementia potential of these candidates and analyze their binding stability with AChE, we used molecular docking integrated with molecular dynamics simulation (a type of kinetic simulation approach that predicts static binding affinity and dynamic complex stability, respectively). Next, based on activity screening results, offline two-dimensional countercurrent chromatography (Offline 2D-CCC) (a separation technique that first groups compounds with similar polarity via 1st-dimensional separation and then purifies each group with optimized solvent systems via 2nd-dimensional separation) was used to isolate the active components. To clarify the inhibitory mechanism of the isolated compounds on AChE, we performed targeted enzymatic kinetics analysis (including determining inhibition type, calculating the half-inhibitory concentration IC₅₀, and measuring the inhibition constant Kᵢ—parameters that characterize how compounds block AChE activity). To systematically confirm the anti-AD mechanism of GJE components and assess potential toxic effects, we applied network pharmacology—a method that constructs “compound-target-disease” interaction networks to reveal multi-component, multi-target, and multi-pathway relationships (instead of focusing on single targets). This approach helped identify cross-talk between GJE’s therapeutic effects and potential toxicity. Nine potential AChEIs were finally screened from GJE: Geniposidic acid, Genipin-1-O-gentiobioside, Gardenoside, Croceic acid, Rutin, Crocin I, Crocin II, Quercetin, and Nevadensin. Their binding energies with AChE (a key parameter for evaluating binding strength) were −8.8, −8.9, −8.2, −8.7, −9.3, −10.4, −10.6, −10.2, and −10.3 kcal/mol, respectively. The terpenoids and flavonoids isolated via Offline 2D-CCC exhibited > 90 % purity (a critical standard for natural product research). Enzymatic kinetics analysis confirmed that these compounds exert reversible AChE inhibition—a property essential for developing safe therapeutic agents for cholinergic dysfunction disorders like AD. To improve the efficiency and accuracy of active compound screening, we combined computer-aided virtual screening (in this study, used to predict compound-AChE binding affinity via molecular docking) with in vitro enzyme inhibition assays. This strategy enabled rapid prioritization of candidates, reduced false-positive results (a common issue with traditional in vitro-only screening), and facilitated targeted preparation of bioactive compounds.