Literature based discovery of alternative TCM medicine for adverse reactions to depression drugs
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RESEARCH
Open Access
Literature based discovery of alternative TCM medicine for adverse reactions to depression drugs Qing Xie, Kyoung Min Yang, Go Eun Heo and Min Song* From The 13th International Workshop on Data and Text Mining in Biomedical Informatics Beijing, China. 3-7 November 2019
* Correspondence: min.song@ yonsei.ac.kr Department of Library and Information Science, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul 03722, Republic of Korea
Abstract Background: In recent years, Traditional Chinese Medicine (TCM) and alternative medicine have been widely used along with western drugs as a complementary form of treatment. In this study, we first use the scientific literature to identify western drugs with obvious side effects. Then, we find TCM alternatives for these western drugs to ameliorate their side effects. Results: We used depression as a case study. To evaluate our method, we showed the relation between herb-ingredients-target-disease for representative alternative herbs of western drugs. Further, a protein-protein interaction network of western drugs and alternative herbs was produced, and we performed enrichment analysis of the targets of the active ingredients of the herbs and examined the enrichment of Gene Ontology terms for Biological Process, Cellular Component, and Molecular Function and KEGG Pathway levels, to show how these targets affect different levels of gene expression. Conclusion: Our proposed method is able to select herbs that are highly relevant to the target indication (depression) and are able to treat the side effects caused by the target drug. The compounds from our selected alternative herbal medicines can therefore be complementary to the western drugs and ameliorate their side effects, which may help in the development of new drugs.
Background Adverse drug reactions (ADR) are undesirable and unintended effects which occur in conjunction with the intended therapeutic effects of a drug. To solve this problem, it is important to the pharmaceutical industries to develop methods to predict potential drug side effects to identify causal relationships with the drugs [1]. Serious adverse drug reactions (SADRs) are reported to be the fourth leading cause of death in the United States, after cancer, stroke and cardiac disorder, and the number of patients experiencing severe and fatal ADR in US hospitals has increased significantly [2]. © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is no
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