Antitumor Compound Identification from Zanthoxylum bungeanum Essential Oil Based on Composition-activity Relationship

The chemical composition of Zanthoxylum bungeanum（Z bungeanum） essential oi1（39 batches） was analyzed by gas chromatography-mass spectrometry（GC-MS） analysis（23 ingredients）, and the antitumor activity against HeLa cells was detected via the MTT[3-（4,5-dimethylthiazol-2-yl）-2,5-diphenyltetrazolium bromide] assay. Two composition-activity relationship（CAR） models, generalized regression neural network（GRNN） and support vector regression（SVR） were respectively used to calculate the mean impact value（MIV） so as to identify bioactive com- pounds. Among them 9 ingredients（peaks 4, 15, 7, 8, 13, 3, 16, 9 and 11） were selected due to their high absolute MIVs. All of them have been confirmed with potential antitumor activity by previous researches. The CAR model combined with MIV was expected to be a credible tool for the active compound identification from herbs.

Live retention database for identification of compounds in capillary gas chromatographic analysis --Principle and structure

A live retention database for compound identification in isothermal and any step temperature programmed capillary gas chromatography has been developed. The database utilizes the Kovats retention indices of compounds on a given stationary phase and the retention time of n-alkanes measured at isothermal conditions on the column to be used, together with the programming parameters. Identification is performed by search operation that compares the calculated results with the retention values of unknown peaks. Cross-reference of the search results of different operating conditions is performed automatically by the database in order to increase the reliability of the identification. The error of the database conversion is ≤± 0.5 index unit, or ≤± 1% on retention time. This paper describes the principle and the structure of the database in detail. The experimental results for different calsses of compounds tested at divers operating conditions will be presented in Part Ⅱ.

Methodology of network pharmacology for research on Chinese herbal medicine against COVID-19:A review

Traditional Chinese medicine,as a complementary and alternative medicine,has been practiced for thousands of years in China and possesses remarkable clinical efficacy.Thus,systematic analysis and examination of the mechanistic links between Chinese herbal medicine(CHM)and the complex human body can benefit contemporary understandings by carrying out qualitative and quantitative analysis.With increasing attention,the approach of network pharmacology has begun to unveil the mystery of CHM by constructing the heterogeneous network relationship of“herb-compound-target-pathway,”which corresponds to the holistic mechanisms of CHM.By integrating computational techniques into network pharmacology,the efficiency and accuracy of active compound screening and target fishing have been improved at an unprecedented pace.This review dissects the core innovations to the network pharmacology approach that were developed in the years since 2015 and highlights how this tool has been applied to understanding the coronavirus disease 2019 and refining the clinical use of CHM to combat it.