In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine
Backgrounds and AimsRecently, a growing number of hepatotoxicity cases aroused by Traditional Chinese Medicine (TCM) have been reported, causing increasing concern. To date, the reported predictive models for drug induced liver injury show low prediction accuracy and there are still no related repor...
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2019-05-01
|
| Series: | Frontiers in Pharmacology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fphar.2019.00458/full |
| _version_ | 1818511085361168384 |
|---|---|
| author | Qihui Wu Qihui Wu Qihui Wu Chuipu Cai Chuipu Cai Pengfei Guo Meiling Chen Xiaoqin Wu Jingwei Zhou Yunxia Luo Yidan Zou Ai-lin Liu Qi Wang Zaoyuan Kuang Jiansong Fang Jiansong Fang |
| author_facet | Qihui Wu Qihui Wu Qihui Wu Chuipu Cai Chuipu Cai Pengfei Guo Meiling Chen Xiaoqin Wu Jingwei Zhou Yunxia Luo Yidan Zou Ai-lin Liu Qi Wang Zaoyuan Kuang Jiansong Fang Jiansong Fang |
| author_sort | Qihui Wu |
| collection | DOAJ |
| description | Backgrounds and AimsRecently, a growing number of hepatotoxicity cases aroused by Traditional Chinese Medicine (TCM) have been reported, causing increasing concern. To date, the reported predictive models for drug induced liver injury show low prediction accuracy and there are still no related reports for hepatotoxicity evaluation of TCM systematically. Additionally, the mechanism of herb induced liver injury (HILI) still remains unknown. The aim of the study was to identify potential hepatotoxic ingredients in TCM and explore the molecular mechanism of TCM against HILI.Materials and MethodsIn this study, we developed consensus models for HILI prediction by integrating the best single classifiers. The consensus model with best performance was applied to identify the potential hepatotoxic ingredients from the Traditional Chinese Medicine Systems Pharmacology database (TCMSP). Systems pharmacology analyses, including multiple network construction and KEGG pathway enrichment, were performed to further explore the hepatotoxicity mechanism of TCM.Results16 single classifiers were built by combining four machine learning methods with four different sets of fingerprints. After systematic evaluation, the best four single classifiers were selected, which achieved a Matthews correlation coefficient (MCC) value of 0.702, 0.691, 0.659, and 0.717, respectively. To improve the predictive capacity of single models, consensus prediction method was used to integrate the best four single classifiers. Results showed that the consensus model C-3 (MCC = 0.78) outperformed the four single classifiers and other consensus models. Subsequently, 5,666 potential hepatotoxic compounds were identified by C-3 model. We integrated the top 10 hepatotoxic herbs and discussed the hepatotoxicity mechanism of TCM via systems pharmacology approach. Finally, Chaihu was selected as the case study for exploring the molecular mechanism of hepatotoxicity.ConclusionOverall, this study provides a high accurate approach to predict HILI and an in silico perspective into understanding the hepatotoxicity mechanism of TCM, which might facilitate the discovery and development of new drugs. |
| first_indexed | 2024-12-10T23:28:43Z |
| format | Article |
| id | doaj.art-3e03b4b86efa4cd1a71e447ee5e20aa9 |
| institution | Directory Open Access Journal |
| issn | 1663-9812 |
| language | English |
| last_indexed | 2024-12-10T23:28:43Z |
| publishDate | 2019-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Pharmacology |
| spelling | doaj.art-3e03b4b86efa4cd1a71e447ee5e20aa92022-12-22T01:29:28ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122019-05-011010.3389/fphar.2019.00458433555In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese MedicineQihui Wu0Qihui Wu1Qihui Wu2Chuipu Cai3Chuipu Cai4Pengfei Guo5Meiling Chen6Xiaoqin Wu7Jingwei Zhou8Yunxia Luo9Yidan Zou10Ai-lin Liu11Qi Wang12Zaoyuan Kuang13Jiansong Fang14Jiansong Fang15Institute of Clinical Pharmacology, Guangzhou University of Chinese Medicine, Guangzhou, ChinaSchool of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, ChinaClinical Research Laboratory, Hainan Province Hospital of Traditional Chinese Medicine, Haikou, ChinaInstitute of Clinical Pharmacology, Guangzhou University of Chinese Medicine, Guangzhou, ChinaSchool of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, ChinaInstitute of Clinical Pharmacology, Guangzhou University of Chinese Medicine, Guangzhou, ChinaSchool of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, ChinaLerner Research Institute, Cleveland Clinic, Cleveland, OH, United StatesInstitute of Clinical Pharmacology, Guangzhou University of Chinese Medicine, Guangzhou, ChinaInstitute of Clinical Pharmacology, Guangzhou University of Chinese Medicine, Guangzhou, ChinaSchool of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, ChinaInstitute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaInstitute of Clinical Pharmacology, Guangzhou University of Chinese Medicine, Guangzhou, ChinaSchool of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, ChinaInstitute of Clinical Pharmacology, Guangzhou University of Chinese Medicine, Guangzhou, ChinaLerner Research Institute, Cleveland Clinic, Cleveland, OH, United StatesBackgrounds and AimsRecently, a growing number of hepatotoxicity cases aroused by Traditional Chinese Medicine (TCM) have been reported, causing increasing concern. To date, the reported predictive models for drug induced liver injury show low prediction accuracy and there are still no related reports for hepatotoxicity evaluation of TCM systematically. Additionally, the mechanism of herb induced liver injury (HILI) still remains unknown. The aim of the study was to identify potential hepatotoxic ingredients in TCM and explore the molecular mechanism of TCM against HILI.Materials and MethodsIn this study, we developed consensus models for HILI prediction by integrating the best single classifiers. The consensus model with best performance was applied to identify the potential hepatotoxic ingredients from the Traditional Chinese Medicine Systems Pharmacology database (TCMSP). Systems pharmacology analyses, including multiple network construction and KEGG pathway enrichment, were performed to further explore the hepatotoxicity mechanism of TCM.Results16 single classifiers were built by combining four machine learning methods with four different sets of fingerprints. After systematic evaluation, the best four single classifiers were selected, which achieved a Matthews correlation coefficient (MCC) value of 0.702, 0.691, 0.659, and 0.717, respectively. To improve the predictive capacity of single models, consensus prediction method was used to integrate the best four single classifiers. Results showed that the consensus model C-3 (MCC = 0.78) outperformed the four single classifiers and other consensus models. Subsequently, 5,666 potential hepatotoxic compounds were identified by C-3 model. We integrated the top 10 hepatotoxic herbs and discussed the hepatotoxicity mechanism of TCM via systems pharmacology approach. Finally, Chaihu was selected as the case study for exploring the molecular mechanism of hepatotoxicity.ConclusionOverall, this study provides a high accurate approach to predict HILI and an in silico perspective into understanding the hepatotoxicity mechanism of TCM, which might facilitate the discovery and development of new drugs.https://www.frontiersin.org/article/10.3389/fphar.2019.00458/fullherb induced liver injuryconsensus modeltraditional chinese medicinehepatotoxicity mechanismin silico |
| spellingShingle | Qihui Wu Qihui Wu Qihui Wu Chuipu Cai Chuipu Cai Pengfei Guo Meiling Chen Xiaoqin Wu Jingwei Zhou Yunxia Luo Yidan Zou Ai-lin Liu Qi Wang Zaoyuan Kuang Jiansong Fang Jiansong Fang In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine Frontiers in Pharmacology herb induced liver injury consensus model traditional chinese medicine hepatotoxicity mechanism in silico |
| title | In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine |
| title_full | In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine |
| title_fullStr | In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine |
| title_full_unstemmed | In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine |
| title_short | In silico Identification and Mechanism Exploration of Hepatotoxic Ingredients in Traditional Chinese Medicine |
| title_sort | in silico identification and mechanism exploration of hepatotoxic ingredients in traditional chinese medicine |
| topic | herb induced liver injury consensus model traditional chinese medicine hepatotoxicity mechanism in silico |
| url | https://www.frontiersin.org/article/10.3389/fphar.2019.00458/full |
| work_keys_str_mv | AT qihuiwu insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT qihuiwu insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT qihuiwu insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT chuipucai insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT chuipucai insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT pengfeiguo insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT meilingchen insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT xiaoqinwu insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT jingweizhou insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT yunxialuo insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT yidanzou insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT ailinliu insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT qiwang insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT zaoyuankuang insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT jiansongfang insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine AT jiansongfang insilicoidentificationandmechanismexplorationofhepatotoxicingredientsintraditionalchinesemedicine |