PURPOSE: This study aimed to investigate the anti-aging potential of CC extracts and fractions, particularly their inhibition of collagenase, MMP-1 and MMP-3 activities in human dermal fibroblasts CCD-966SK, followed by isolation, identification and analysis of their bioactive constituents.

STUDY DESIGN AND METHODS: DPPH assay was firstly used to evaluate the antioxidant activity throughout the bioactivity-guided fractionation. Cell viability was determined using MTS assay. Collagenase activity was examined, while MMP-1 and MMP-3 expression were measured using qRT-PCR and western blotting. Then, chemical identification of pure compounds isolated from CC fractions was done by using ESIMS, 1H and 13C NMR spectroscopies. HPLC analyses were carried out for bioactive fractions to quantify the major components.

RESULTS: Throughout the antioxidant activity-guided fractionation, fractions CC-E2 and CC-E3 with antioxidant activity and no toxicity towards CCD-966SK cells were obtained from CC 75% ethanol partitioned layer (CC-E). Both fractions inhibited collagenase activity, MMP-1 and MMP-3 mRNA and protein expression, as well as NF-κB activation induced by TNF-α in CCD-966SK cells. 14 compounds, which mainly consists of flavonoids and their glycosides, were isolated. Quercitrin (14.79% w/w) and quercetin (11.20% w/w) were major compounds in CC-E2 and CC-E3, respectively, as quantified by HPLC. Interestingly, both fractions also inhibited the MMP-3 protein expression synergistically, compared with treatment alone.

OBJECTIVE: The aim of the in silico study was to establish protocols to predict the most effective flavonoid from prenylated and pyrano-flavonoid classes for AChE inhibition linking to the potential treatment of Alzheimer's disease.

METHODOLOGY: Three flavonoids isolated from Artocarpus anisophyllus Miq. were selected for the study. With these compounds, Lipinski filter, ADME/Tox screening, molecular docking and quantitative structure-activity relationship (QSAR) were performed in silico. In vitro activity was evaluated by bioactivity staining based on the Ellman's method.

RESULTS: In the Lipinski filter and ADME/Tox screening, all test compounds produced positive results, but in the target fishing, only one flavonoid could successfully target AChE. Molecular docking was performed on this flavonoid, and this compound gained the score as -13.5762. From the QSAR analysis the IC50 was found to be 1659.59 nM. Again, 100 derivatives were generated from the parent compound and docking was performed. The derivative compound 20 was the best scorer, i.e. -31.6392 and IC50 was predicted as 6.025 nM.

METHODS: In this study, the chronotherapeutic effect of fisetin on ammonium chloride (AC)-induced hyperammonaemic rats was investigated, to ascertain the time point at which the maximum drug effect is achieved. The anti-hyperammonaemic potential of fisetin (50mg/kg b.w. oral) was analysed when administered to AC treated (100mg/kg b.w. i.p.) rats at 06:00, 12:00, 18:00 and 00:00h. Amelioration of pathophysiological conditions by fisetin at different time points was measured by analysing the levels of expression of liver urea cycle enzymes (carbamoyl phosphate synthetase-I (CPS-I), ornithine transcarbamoylase (OTC) and argininosuccinate synthetase (ASS)), nuclear transcription factor kappaB (NF-κB p65), brain glutamine synthetase (GS) and inducible nitric oxide synthase (iNOS) by Western blot analysis.

RESULTS: Fisetin increased the expression of CPS-I, OTC, ASS and GS and decreased iNOS and NF-κB p65 in hyperammonaemic rats. Fisetin administration at 00:00h showed more significant effects on the expression of liver and brain markers, compared with other time points.

METHOD: The SARS-CoV receptor structure files (viral structural components) were retrieved from the Protein Data Bank (PDB) database: membrane protein (PDB ID: 3I6G), main protease (PDB ID: 5RE4), and spike glycoproteins (PDB ID: 6VXX and 6VYB). The receptor binding pocket regions were identified by Discovery Studio (BIOVIA) for targeted docking with TBF polyphenols (genistin, kaempferol, mellein, rhoifolin and scutellarein). The ligand and SARS-CoV family receptor structure files were pre-processed using the AutoDock tools. Molecular docking was performed with the Lamarckian genetic algorithm using AutoDock Vina 4.2 software. The best pose (ligand-receptor complex) from the molecular docking analysis was selected based on the minimum binding energy (MBE) and extent of structural interactions, as indicated by BIOVIA visualization tool. The selected complex was validated by a 100 ns MD simulation run using the GROMACS software. The dynamic behaviour and stability of the receptor-ligand complex were evaluated by the root mean square displacement (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), solvent accessible surface volume (SASV) and number of hydrogen bonds.