Network pharmacology provides new insights into the mechanism of traditional Chinese medicine and natural products used to treat pulmonary hypertension.

Background: Pulmonary hypertension (PH) is a rare cardiovascular disease with high morbidity and mortality rates. It is characterized by increased pulmonary arterial pressure. Current research into relevant therapeutic drugs and targets for PH, however, is insufficient still. Traditional Chinese medicine (TCM) and natural products have a long history as therapeutics for PH. Network pharmacology is an approach that integrates drug-target interactions and signaling pathways based on biomarkers information obtained from drug and disease databases. The concept of network pharmacology shows many similarities with the TCM philosophy. Network pharmacology help elucidate the mechanisms of TCM in PH. This review presents representative applications of network pharmacology in the study of the mechanisms of TCM and natural products for the treatment of PH.

Methods: In this review, we used ("pulmonary hypertension" OR "pulmonary arterial hypertension" OR "chronic thromboembolic pulmonary hypertension") AND ("network pharmacology" OR "systematic pharmacology") as keywords to search for reports from PubMed, Web of Science, and Google Scholar databases from ten years ago. The studies were screened and those chosen are summarized here. The TCM and natural products inPH and their corresponding targets and signaling pathways are described. Additionally, we discuss the application of network pharmacology in the study of TCM in PH to provide insights for future application strategies.

Results: Network pharmacology have shown that AKT-related pathways, HIF-1 signaling pathway, MAPK signaling pathway, TGF-β-Smad pathway, cell cycle-related pathways and inflammation-related pathways are the main signaling pathways enriched in the PH targets of TCM. Reservatrol, curcumol, genistin, formononetin, wogonin, luteolin, baicalein, berberine, triptolide and tanshinone llA are active ingredients specific for PH treatment. A number of databases and tools specific for the treatment of PH are used in network pharmacology and natural product research.

Conclusion: Through the reasonable combination of molecular docking, omics technology and bioinformatics technology, the mechanism of multi-targets can be explained more comprehensively. Analyzing the complex mechanism of TCM from the clinical perspective may be a potential development trend of network pharmacology. Combination of predicted targets and traditional pharmacology improves efficiency of drug development.