China Pharmaceutical University researchers have created HerbSyner_Finder, a computational framework that identifies synergistic herbal ingredient combinations for complex diseases, offering potential for multi-target therapeutic development.
Researchers at China Pharmaceutical University have developed a computational framework designed to identify synergistic combinations of herbal medicine ingredients, potentially accelerating the development of safer and more effective treatments for complex diseases.
The new platform, known as HerbSyner_Finder, was created by a research team led by Professor Yinyin Wang and Professor Ninghua Tan. The system is designed to tackle one of the biggest challenges in herbal medicine research: identifying beneficial ingredient combinations from thousands of possible candidates.
Herbal medicines are often believed to work through the interaction of multiple compounds rather than a single active ingredient. However, understanding how these compounds work together has remained difficult because of the complexity of biological systems and the large number of possible interactions.
The HerbSyner_Finder platform addresses this problem by constructing what researchers describe as a multidimensional combinatorial atlas. The framework analyses interactions between herbs, ingredients and disease targets to identify combinations most likely to work synergistically.
Asthma treatments used to test the system
To validate the platform, researchers applied it to five established herbal prescriptions used to treat cough variant asthma (CVA), a chronic inflammatory airway disease.
CVA is commonly treated using inhaled corticosteroids, but long-term use can carry safety risks and side effects, increasing interest in alternative therapies with lower toxicity.
Using network proximity calculations and Louvain community detection modelling, the system found two ingredient combinations from thousands of possibilities: kaempferol-quercetin and berberine-luteolin.
CVA is commonly treated using inhaled corticosteroids, but long-term use can carry safety risks and side effects
Researchers then carried out laboratory experiments to test the predicted combinations.
In vitro studies using RAW264.7 macrophages and airway smooth muscle cells showed that low-dose berberine-luteolin significantly reduced inflammatory responses and abnormal cell proliferation.
According to the researchers, the effect was comparable to high-dose dexamethasone, a commonly used steroid treatment.
Several recognised synergy assessment models, including ZIP, Loewe, HSA and Bliss analyses, confirmed strong synergistic activity between the compounds.
Reduced inflammation and improved outcomes
The team also tested the ingredient combination in rat models of cough variant asthma induced using ovalbumin.
Results showed that the combined treatment significantly reduced cough frequency, eased airway inflammation and lowered mucus overproduction and collagen deposition in lung tissue.
The researchers found the combined compounds outperformed individual ingredients in suppressing inflammatory cytokines including TNF-α, IL-1β and IL-6, which are associated with chronic airway inflammation.
Results showed that the combined treatment significantly reduced cough frequency, eased airway inflammation and lowered mucus overproduction and collagen deposition in lung tissue
Further mechanistic analysis revealed that berberine-luteolin worked by suppressing the NLRP3/NF-κB signalling pathway, an important regulator of inflammation and immune responses.
The combination also reduced phosphorylation of p65 and IκBα while downregulating chemokines linked to cough variant asthma, including CXCL10, CXCL3 and CCR10.
Open-access platform for broader disease research
Researchers said the framework could have applications beyond herbal medicine and asthma treatment.
Because HerbSyner_Finder functions as a universal analytical tool, it could potentially be adapted to study other complex diseases where multi-target therapies may offer advantages over single-drug approaches.
The platform has been made openly available through GitHub and a dedicated web server, herbcomb.com, allowing broader access for researchers working in systems pharmacology, drug discovery and integrative medicine.
The research team believes the framework could help accelerate the identification of synergistic therapeutic combinations with lower side effects while improving understanding of how complex natural medicines function at a molecular level.
They added that the approach may support the future development of more personalised and biologically targeted treatments for inflammatory and chronic diseases.
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