Discovery of Herbal Pairs Containing Gastrodia elata Based on Data Mining and the Delphi Expert Questionnaire and Their Potential Effects on Stroke through Network Pharmacology

• Main Authors: Rongrong Zhou, Yan Zhu, Wei Yang, Fengrong Zhang, Junwen Wang, Runhong Yan, Shihuan Tang, Zhiyong Li
• Format: Article
• Language: English
• Published: Hindawi Limited 2020-01-01
• Series: Evidence-Based Complementary and Alternative Medicine
• Online Access: http://dx.doi.org/10.1155/2020/4263591

Background. Traditional Chinese medicine (TCM) formulae can be regarded as a source of new antistroke drugs. The aim of this study was to discover herbal pairs containing Gastrodia elata (Tianma, TM) from formulae based on data mining and the Delphi expert questionnaire. The proposed approach for discovering new herbal combinations, which included data mining, a clinical investigation, and a network pharmacology analysis, was evaluated in this study. Methods. A database of formulae containing TM was established. All possible herbal pairs were acquired by data mining association rules, and herbal pairs containing TM were screened according to the Support and Confidence levels. Taking stroke as the research object, the relationships between herbal pairs containing TM and stroke were explored by the Delphi expert questionnaire and statistical methods. To explore the effects of herbal pairs containing TM on stroke, a network pharmacology analysis was performed to predict core targets, biological functions, pathways, and mechanisms of action. Results. A total of 1903 formulae containing TM, involving 896 Chinese herbal medicines (CHMs) and 126 herbal pairs containing RG, were analyzed by association rules. A total of 27 herbal pairs were further screened according to the Support and Confidence levels. Twelve herbal pairs containing RG were added according to the expert questionnaires. Weightiness analysis showed that 9 groups of core herbal pairs contained RG, including TM-QX, TM-JH, TM-CX, TM-GG, TM-SJM, TM-JC, TM-SCP, TM-MJZ, and TM-GT. Two core herbal pairs, TM-JH and TM-CX, were randomly screened to explore their network pharmacological mechanisms in stroke. The important biological targets for network pharmacological analysis of TM-CX and TM-JH related to stroke were PTGS2, ACE, APP, NOS1, and NOS2. An herbal pair-compound-core target-pathway network (H-C-T-P network) was established, and arginine biosynthesis, arginine and proline metabolism, and the relaxin signaling pathway were identified by enrichment analysis. Conclusion. The herbal pairs of TM-CX and TM-JH obtained from data mining and the expert investigation were found to have effects of preventing and treating stroke through network pharmacology. This could be a viable approach to uncover hidden knowledge about TCM formulae and to discover herbal combinations with clinical and medicinal value based on data mining and questionnaires.