ArticleBiomolecules2019
A Computational Toxicology Approach to Screen the Hepatotoxic Ingredients in Traditional Chinese Medicines:
Article in Biomolecules, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 41 citations in OpenAlex.
- Integrating Artificial Intelligence Into Drug Discovery From Medicinal Plants: Current Applications and Infrastructural Challenges.Chemical biology & drug design · 2026Review
- Hepatotoxicity prediction for traditional Chinese medicine: a two-step in silico framework integrating network and machine learning approaches.BMC complementary medicine and therapies · 2026Article
- Development and application of artificial intelligence in traditional Chinese medicine research and development.Chinese medicine · 2026Review
- Effective Components and Molecular Mechanism of Biejiaruangan Capsule Against Liver Fibrosis: High-resolution Mass Spectrometry, Network Pharmacological Analysis and Experimental Verification.Combinatorial chemistry & high throughput screening · 2026Article
- Emodin and physcion alleviate cholestatic liver injury by targeting FXR: hepatoprotective components identified in processedFrontiers in pharmacology · 2025Article
- Application and research progress on artificial intelligence in the quality of Traditional Chinese Medicine.Frontiers in pharmacology · 2025Review
- Traditional, complementary, and integrative medicine and artificial intelligence: Novel opportunities in healthcare.Integrative medicine research · 2024Article
- Centipeda minima active components and mechanisms in lung cancer.BMC complementary medicine and therapies · 2023Article
- Unraveling the mystery of efficacy in Chinese medicine formula: New approaches and technologies for research on pharmacodynamic substances.Arabian journal of chemistry · 2022Review
- Natural Products for Liver Cancer Treatment: From Traditional Medicine to Modern Drug Discovery.Nutrients · 2022Review
- The Use of Artificial Intelligence in Complementary and Alternative Medicine: A Systematic Scoping Review.Frontiers in pharmacology · 2022Article
- Detoxification technology and mechanism of processing withFrontiers in pharmacology · 2022Article
- Hepatic Organoid-Based High-Content Imaging Boosts Evaluation of Stereoisomerism-Dependent Hepatotoxicity of Stilbenes in Herbal Medicines.Frontiers in pharmacology · 2022Article
- Artificial intelligence to deep learning: machine intelligence approach for drug discovery.Molecular diversity · 2021Review
- Integrated Strategy of Network Pharmacological Prediction and Experimental Validation Elucidate Possible Mechanism of Bu-Yang Herbs in Treating Postmenopausal Osteoporosis via ESR1.Frontiers in pharmacology · 2021Article
- Herb-Induced Liver Injury Related toFrontiers in pharmacology · 2021Review
- A review on machine learning approaches and trends in drug discovery.Computational and structural biotechnology journal · 2021Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, liver injury induced by Traditional Chinese Medicines (TCMs) has gained increasing attention worldwide. Assessing the hepatotoxicity of compounds in TCMs is essential and inevitable for both doctors and regulatory agencies. However, there has been no effective method to screen the hepatotoxic ingredients in TCMs available until now. In the present study, we initially built a large scale dataset of drug-induced liver injuries (DILIs). Then, 13 types of molecular fingerprints/descriptors and eight machine learning algorithms were utilized to develop single classifiers for DILI, which resulted in 5416 single classifiers. Next, the NaiveBayes algorithm was adopted to integrate the best single classifier of each machine learning algorithm, by which we attempted to build a combined classifier. The accuracy, sensitivity, specificity, and area under the curve of the combined classifier were 72.798, 0.732, 0.724, and 0.793, respectively. Compared to several prior studies, the combined classifier provided better performance both in cross validation and external validation. In our prior study, we developed a herb-hepatotoxic ingredient network and a herb-induced liver injury (HILI) dataset based on pre-clinical evidence published in the scientific literature. Herein, by combining that and the combined classifier developed in this work, we proposed the first instance of a computational toxicology to screen the hepatotoxic ingredients in TCMs. Then
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