Network Pharmacology of Medicinal Plants in Cardiometabolic Disorders: A Narrative Review of Molecular Networks, Validation Evidence, and Translational Challenges

Abstract

Background: Cardiometabolic disorders arise from interconnected disturbances involving inflammation, oxidative stress, insulin resistance, endothelial dysfunction, mitochondrial impairment, lipid dysregulation, apoptosis, and tissue remodeling. Medicinal plants contain multiple bioactive constituents that may influence several of these mechanisms simultaneously, making network pharmacology a potentially useful framework for systems-level natural-product research. Objective: To critically synthesize the principles, computational resources, analytical workflows, reported molecular networks, validation levels, and translational limitations of medicinal-plant network pharmacology in type 2 diabetes mellitus, hypertension, coronary artery disease, heart failure, and atherosclerosis. Methods: A narrative-review approach was used to integrate foundational methodological publications, database and software reports, computational target-prediction studies, molecular-docking and molecular-dynamics investigations, ADMET analyses, experimental studies, clinical investigations, and authoritative reviews. Evidence was organized by analytical stage, phytochemical class, disease area, recurrent molecular target, signaling pathway, and depth of validation. Computational predictions were interpreted as hypothesis-generating, whereas in vitro, in vivo, and human studies were considered progressively stronger levels of validation. No meta-analysis or formal risk-of-bias assessment was undertaken because of substantial methodological and clinical heterogeneity. Results: Recurrently reported targets included AKT1, TNF, IL6, VEGFA, PPARG, NOS3, MAPK proteins, RELA, TP53, and CASP3. Common pathways included PI3K/Akt, AMPK, MAPK, NF-κB, AGE–RAGE, HIF-1, Nrf2, apoptosis, calcium signaling, and renin–angiotensin–aldosterone signaling. Berberine, Salvia miltiorrhiza, Astragalus-derived compounds, ginsenosides, Compound Danshen Dripping Pills, Qishen Yiqi Dropping Pills, and Yiqi Fumai Injection had evidence extending beyond computational prediction. Nevertheless, most studies remained limited to database analysis, enrichment, docking, or preclinical validation, and repeated pathway identification was vulnerable to database and topology-related bias. Conclusion: Network pharmacology is valuable for prioritizing medicinal-plant compounds, targets, and pathways, but it does not independently establish therapeutic efficacy. Translation requires standardized phytochemical characterization, reproducible analysis, direct target validation, pharmacokinetic and safety assessment, herb–drug interaction evaluation, and rigorous human studies