Classification of Mixtures of Chinese Herbal Medicines Based on a Self-organizing Map (SOM)

Maolin Wang; Li Li; Changyuan Yu; Aixia Yan; Zhongzhen Zhao; Ge Zhang; Miao Jiang; Aiping Lu; Johann Gasteiger

doi:10.1002/minf.201500115

Classification of Mixtures of Chinese Herbal Medicines Based on a Self-organizing Map (SOM)

Mol Inform. 2016 Apr;35(3-4):109-15. doi: 10.1002/minf.201500115. Epub 2016 Jan 6.

Authors

Maolin Wang^{1

2}, Li Li², Changyuan Yu¹, Aixia Yan³, Zhongzhen Zhao⁴, Ge Zhang⁴, Miao Jiang⁵, Aiping Lu^{2

4

6}, Johann Gasteiger⁷

Affiliations

¹ State Key Laboratory of Chemical Resource Engineering, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China, State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, P. O. Box 53, Beijing University of Chemical Technology, 15 BeiSanHuan East Road, Beijing 100029, PR China.
² Institute of Basic Research in Clinical Medicine, China Academy of Traditional Chinese Medicine, Beijing 100700, China, Institute of Basic Research In Clinical Medicine, China Academy of Traditional Chinese Medicine, Nanxiaojie 16#, Dongzhimennei, Beijing 100700, China. Tel.: +86 10 64014411 EXT 2397; Fax: +86 10 84032881 addresses: .
³ State Key Laboratory of Chemical Resource Engineering, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China, State Key Laboratory of Chemical Resource Engineering, Department of Pharmaceutical Engineering, P. O. Box 53, Beijing University of Chemical Technology, 15 BeiSanHuan East Road, Beijing 100029, PR China. yanax@mail.buct.edu.cn.
⁴ School of Chinese Medicine, Hong Kong Baptist University, Kowloon, Hong Kong.
⁵ Institute of Basic Research in Clinical Medicine, China Academy of Traditional Chinese Medicine, Beijing 100700, China, Institute of Basic Research In Clinical Medicine, China Academy of Traditional Chinese Medicine, Nanxiaojie 16#, Dongzhimennei, Beijing 100700, China. Tel.: +86 10 64014411 EXT 2397; Fax: +86 10 84032881 addresses: .. miao_jm@vip.126.com.
⁶ E-institute of Shanghai Municipal Education Commission, Shanghai TCM University, Shanghai 201203, China.
⁷ Computer-Chemie-Centrum and Institute of Organic Chemistry, University of Erlangen-Nürnberg, 91052 Erlangen, Germany.

PMID: 27491920
DOI: 10.1002/minf.201500115

Abstract

Chinese Herbal Medicines (CHMs) are typically mixtures of compounds and are often categorized into cold and hot according to the theory of Chinese Medicine. This classification is essential for guiding the clinical application of CHMs. In this study, three types of molecular descriptors were used to build models for classification of 59 CHMs with typical cold/hot properties in the training set taken from the original records on properties in China Pharmacopeia as reference. The accuracy and the Matthews correlation coefficient of the models were validated by a test set containing other 56 CHMs. The best model produced the accuracies of 94.92 % and 83.93 % on training set and test set, respectively. The MACCS fingerprint model is robust in predicting hot/cold properties of the CHMs from their major constituting compounds. This work shows how a classification model for data consisting of multi-components can be developed. The derived model can be used for the application of Chinese herbal medicines.

Keywords: Chinese Herbal Medicines; Classification model; Classification of mixtures; cold and hot properties; self-organizing map.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
China
Drugs, Chinese Herbal / classification*
Medicine, Chinese Traditional
Models, Theoretical

Substances

Drugs, Chinese Herbal