Bitter-Pungent Flavor Identification Based on Ingredient Information Similarity of Chinese Herbal Medicines

Background: The flavor theory of Chinese herbal medicines (CHMs) is one of the core theories of traditional Chinese medicine (TCM). Accurate flavor identification of CHMs is essential to guide the clinical application of CHMs. Objective: To develop a new method for flavor identification of CHMs according to the ingredient information for CHMs. Methods: It was found that the chemical basis of medicinal flavors was CHM ingredients. We developed a bitter-pungent flavor identification scheme to build a relationship between medicinal flavors and CHM ingredients. We firstly proposed a scientific hypothesis that "CHMs with similar flavors should have a similar chemical basis". To test this scientific hypothesis, we then explored an intelligent algorithm for bitter-pungent flavor identification of CHMs based on the information similarity of CHM ingredients. GC was used to separate the chemical ingredients of CHMs and analyze the ingredient information of CHMs. A distance metric learning algorithm was built to measure the similarity of GC chemical fingerprints. A bitter-pungent flavor identification scheme (BPFI) was proposed to predict the bitter-pungent flavor of CHMs. Finally, a number of experiments were performed to evaluate the identification performance of our scheme. Results: Compared to classical algorithms, our proposed BPFI scheme has better flavor prediction performance. The total identification accuracy of our BPFI scheme reached 0.843. The area under ROC (receiver operating characteristic curve) curve (AUC) was 0.899. Conclusion: The experimental results confirmed our inference that the chemical basis of CHM flavors was CHM ingredients, and implied that CHMs with similar flavors had similar composition. The BPFI model proved to be effective and feasible. Highlights: Verification hypothesis: CHMs with similar flavors should have similar chemical basis.