Integrating network pharmacology and multidimensional bioinformatics: Mechanistic exploration of six food and medicine homology plants in coronary heart disease therapy.

Researchers investigated how six traditional Chinese medicinal plants—used both as food and medicine—may help treat coronary heart disease (CHD), a condition where arteries become narrowed or blocked. Using advanced computer modeling and biological databases, scientists identified 119 active compounds from these plants and examined how they interact with 951 potential targets in the body. The study found 60 key therapeutic targets that may help explain how these plants work. The research revealed that these medicinal plants appear to work through multiple mechanisms, particularly by modulating immune system responses and reducing inflammation. Four key genes were identified as especially important, showing causal relationships with heart disease. The plants' active compounds demonstrated strong binding abilities to critical protein targets involved in CHD development, and computer simulations confirmed these interactions remained stable over time. The analysis also showed these compounds affect specific immune cells, including activated memory T cells and naïve B cells, suggesting they help regulate immune responses that contribute to heart disease. The pathways identified relate to how the body responds to inflammation-causing substances and controls programmed cell death. This research provides scientific evidence for how traditional food-medicine plants may complement conventional CHD treatments through their multi-component, immune-regulating effects, though clinical trials in humans are still needed to confirm these benefits. Patients interested in herbal approaches should consult with a qualified traditional Chinese medicine practitioner.

This computational study employed network pharmacology, WGCNA, and machine learning to elucidate mechanisms of six food and medicine homology plants (FMHPs) in CHD treatment. Researchers identified 119 bioactive compounds and 951 associated targets from TCMSP, SwissTargetPrediction, and Herb databases. Integration with GSE42148 dataset DEGs yielded 60 therapeutic targets. PPI network construction and GO/KEGG enrichment analyses revealed significant involvement in lipopolysaccharide response and apoptotic signaling pathways. Four hub genes were identified through three independent machine learning algorithms, with Mendelian randomization confirming causal CHD associations. Immune infiltration analysis demonstrated regulatory effects on CD4+ memory activated T cells and naïve B cells. Molecular docking confirmed favorable binding affinities between core compounds and hub targets, while molecular dynamics simulations validated complex stability. ADMET predictions supported drug-like properties. Findings provide mechanistic framework for FMHPs' immunomodulatory and multi-target therapeutic effects in CHD, supporting their potential integration into clinical practice.