Identification of anti-inflammatory compounds from Zhongjing formulae by knowledge mining and high-content screening in a zebrafish model of inflammatory bowel diseases.

ABSTRACT:

Background

Inflammatory bowel diseases (IBD) are chronic relapsing intestinal inflammations with increasing global incidence, and new drug development remains in urgent demand for IBD management. To identify effective traditional Chinese medicine (TCM) formulae and compounds in IBD treatment, we innovatively combined the techniques of knowledge mining, high-content screening and high-resolution mass spectrometry, to conduct a systematic screening in Zhongjing formulae, which is a large collection of TCM prescriptions with most abundant clinical evidences.

Methods

Using Word2vec-based text learning, the correlations between 248 Zhongjing formulae and IBD typical symptoms were analyzed. Next, from the top three formulae with predicted relationship with IBD, TCM fractions were

SUBMITTER: Yu Y 

PROVIDER: S-EPMC8166029 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature