METHODS: OVX rats were treated with TPEE at 125, 250, 500 mg/kg/day, or controls (pomegranate extract, 500 mg/kg/day; estradiol, 25 μg/kg/day) for 12 weeks. Gut microbiota analysis was conducted by extracting the microbial DNA from fecal samples and microbiome taxonomic profiling was carried out by using next-generation sequencing. The levels of serum biomarkers were analyzed using enzyme-linked immunosorbent assay (ELISA) kit. The prediction of functional biomarker of microbiota was performed using PICRUSt to investigate the potential pathways associated with gut health and serum lipid profile regulation. To study the correlation between gut microbiota composition and serum lipid levels, Spearman's correlation coefficients were defined and analyzed. Additionally, gas chromatography-mass spectrometry analysis was conducted to uncover additional physiologically active ingredients.
RESULTS: TPEE-treated OVX rats showed significant reduction in serum triglycerides (TG), total cholesterols (TCHOL), and LDL/VLDL levels but increase in HDL level. The alteration in the pathways involve in metabolism was the most common among the other KEGG categories. Particularly, TPEE also significantly reduced the relative abundance of sequences read associated with inflammatory bowel disease (IBD) and the peroxisome proliferator-activated receptor (PPAR) signalling pathway. TPEE intervention was seen to reduce the Firmicutes to Bacteroidetes (F/B) ratio in the OVX rats, denoting a reduction in microbial dysbiosis in the OVX rats. Correlation analysis at the phylum level revealed that Bacteriodetes and Proteobacteria were strongly correlated with serum TG, TCHOL and HDL levels. At the species level, Bifidobacterium pseudolongum group was seen to positively correlate with serum HDL level and negatively correlated with serum AST, ALT, LDL/VLDL, TCHOL, and TG levels.
CONCLUSIONS: TPEE treatment showed therapeutic benefits by improving the intestinal microbiota composition which strongly correlated with the serum lipid and cholesterol levels in the OVX rats.
CONCLUSION: This review will provide information on the causes and indicators of skin aging as well as examine studies that have used plants to produce anti-aging products.
OBJECTIVES: Here, we explored the phytochemical diversity of the seven varieties from Peninsular Malaysia using Nuclear Magnetic Resonance (NMR) and Liquid Chromatography-Mass Spectrometry (LC-MS) analyses and correlated it with the α-glucosidase inhibitory activity.
METHODOLOGY: The Nuclear Overhauser Effect Spectroscopy (NOESY) One-Dimensional (1D)-NMR and LC-MS data were processed, annotated, and correlated with in vitro α-glucosidase inhibitory using multivariate data analysis.
RESULTS: The α-glucosidase results demonstrated that different varieties have varying inhibitory effects, with the highest inhibition rate being F. deltoidea var. trengganuensis and var. kunstleri. Furthermore, diverse habitats and plant ages could also influence the inhibitory rate. The heat map from NMR and LC-MS profiles showed unique patterns according to varying levels of α-glucosidase inhibition rate. The Partial Least Squares (PLS) model constructed from both NMR and LC-MS further confirmed the correlation between the α-glucosidase inhibition rate of F. deltoidea varieties and its metabolite profiles. The Variable Influence on Projection (VIP) and correlation coefficient (p(corr)) values values were used to determine the highly relevant metabolites for explaining the anticipated inhibitory action.
CONCLUSION: NMR and LC-MS annotations allow the identification of flavan-3-ols and proanthocyanidins as the key bioactive factors. Our current results demonstrated the value of multivariate data analysis to predict the quality of herbal materials from both biological and chemical aspects.
METHODOLOGY: The research encompassed the selection of proteins from the Protein Data Bank (PDB), followed by structural refinement processes and optimization. Ligands such as Karanjin and standard drugs were retrieved from PubChem, followed by a comprehensive analysis of their ADMET profiling and pharmacokinetic properties. Protein-ligand interactions were evaluated through molecular docking using AutoDockTools 1.5.7, followed by the analysis of structural stability using coarse-grained simulations with CABS Flex 2.0. Molecular dynamics simulations were performed using Desmond 7.2 and the OPLS4 force field to explore how Karanjin interacts with proteins over 100 nanoseconds, focusing on the dynamics and structural stability.
RESULTS: Karanjin, a phytochemical from Pongamia pinnata, shows superior drug candidate potential compared to common medications, offering advantages in efficacy and reduced side effects. It adheres to drug-likeness criteria and exhibits optimal ADMET properties, including moderate solubility, high gastrointestinal absorption and blood-brain barrier penetration. Molecular docking revealed Karanjin's highest binding energy against receptor 3L2M (Pig pancreatic alpha-amylase) at -9.1 kcal/mol, indicating strong efficacy potential. Molecular dynamics simulations confirmed stable ligand-protein complexes with minor fluctuations in RMSD and RMSF, suggesting robust interactions with receptors 3L2M.
CONCLUSION: Karanjin demonstrates potential in pharmaceutical expansion for treating metabolic disorders such as diabetes, as supported by computational analysis. Prospects for Karanjin in pharmaceutical development include structural modifications for enhanced efficacy and safety. Nanoencapsulation may improve bioavailability and targeted delivery to pancreatic cells, while combination therapies could optimize treatment outcomes in diabetes management. Clinical trials and experimental studies are crucial to validate its potential as a novel therapeutic agent.