A MS-feature-based medicinal plant database-driven strategy for ingredient identification of Chinese medicine prescriptions

Abstract

Identification of the individual herbs that constitute the Chinese medicine prescription (CMP) is a key step to control the quality and ensure the efficacy of traditional Chinese medicine (TCM), but also a challenging task for analysts from all over the world. In this study, a MS-feature-based medicinal plant database-driven strategy was proposed for quick and automatic interpretation of CMP ingredients. The single herb database consisting of stable ions of sixty-one common TCM medicinal herbs was first constructed. And then, the data of CMP was imported into a self-built searching program to achieve quick and automatic identification with four steps including level 1 candidate herb screening based on stable ions (step 1), level 2 candidate herb screening based on unique ions (step 2), difficult-to-distinguish herb differentiation (step 3) and results integration (step 4). The identification model was optimized and validated with homemade Shaoyaogancao Decoction, Mahuang Decoction, Banxiaxiexin Decoction, and their related negative prescriptions and homemade fakes. Another nine batches of homemade and commercial CMPs were applied to this new approach and most of composed herbs in the corresponding CMPs were correctly identified. This work provided a promising and universal strategy for the clarification of CMP ingredients.

Keywords: Chinese medicine prescription; Ingredient identification; UPLC-Q/TOF.