Frontiers in Computational Chemistry

Volume: 6

Advances in Computational Network Pharmacology for Traditional Chinese Medicine (TCM) Research

Author(s): Yu-Xi Huang, Shi-Jun Yue*, Wen-Xiao Wang and Yu-Ping Tang * .

Pp: 193-234 (42)

DOI: 10.2174/9789815036848122060007

* (Excluding Mailing and Handling)

Abstract

Traditional Chinese Medicine (TCM) is a complementary and alternative medicine but possesses remarkable clinical efficacy in China and surrounding countries. Hence, systematic analysis and elucidation of the complex chemical basis and action mechanisms of TCM will be highly beneficial. Nowadays, the widespread application of network pharmacology has unveiled the mystery of TCM to some extent by constructing the relationship of “herb-compound-target-disease”. Moreover, it can promote the development of drug discovery, medical guidance, and the dissection of the syndrome in TCM. With the integration of computational techniques into network pharmacology, the efficiency of data mining and the accuracy of active compounds identification and target fishing have been improved, and the “herb-compound-targt- disease” network has been more systematically and comprehensively explained to reflect the holistic mechanisms of TCM. Therefore, a comprehensive overview of each aspect of the use of computational techniques in TCM network pharmacology is urgent. This chapter systematically dissects the core contents involved in TCM computational network pharmacology and highlights its application on TCM against COVID-19, and severs the cutting-edge study examples to compare and analyze the advantages and limitations of different computational techniques.


Keywords: Algorithms, COVID-19, Molecular modeling, Network pharmacology, Traditional Chinese medicine.

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