In Vivo and Network Pharmacology Based Molecular Screening of Potential Compounds From Cassia Absus Seeds Against Hyperlipidemia
Year: 2025
Type: article
Abstract: Background: Medicinal plants are valuable sources of bioactive chemicals with multi-target effects. Cassia absus, traditionally used to treat various ailments such as conjunctivitis, tumours, and hepatic disorders, was investigated for its anti-hyperlipidemic potential—a major risk factor for hypertension and cardiovascular diseases. Objectives: To prepare C. absus seeds extract in methanol and measure their efficacy against hyperlipidemia in selected rat groups. To identify the bioactive, drug-like compounds using network pharmacology and molecular docking. Methodology: Rats were divided into four groups: control on a normal diet (T0), hyperlipidemic group on a fat-rich diet (T1), atorvastatin-treated group (T2), and seeds extract-treated group (T3). Lipid levels were measured on days 0, 7 and 14. Active compounds in C. absus seeds were identified using databases and screened for drug-likeness by Lipinski's Rule and Swiss ADME. Swiss TargetPrediction, GeneCards and NCBI identified compounds and disease-targeted genes. Compounds-target interacting genes were identified via Venn diagram. Protein-protein interaction created by STRING, DAVID provided functional gene annotations and KEGG Pathways. Compound-target-pathway networks visualized using Cytoscape, with molecular docking predicted binding affinity. Results: The T3 group showed a significant improvement in lipid profile, with a reduction in TC (47.2%), triglycerides (53.4%), LDL (61.7%), and an elevated HDL (51.5%). A study identified six anti-hyperlipidemic compounds, including 4,6-dimethyl mannose, methyl gallate, and syringic acid. Strong binding affinity observed between ALB1, PPARG, and ESR1 proteins. Most interacting disease-targeted pathways were also identified. Conclusion: The study supported the anti-hyperlipidemic potential of C. absus seeds and their drug-like compounds through network pharmacology, thus paving the way for the development of herbal medicine.
Authors: Ayesha Chaudary, Sumaira Mehboob, Muhammad Saadat Abbas, Niaz Muhammad
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4415981433
FWCI:
Cites:
Cited by:
Related to: