ArticleMolecules (Basel, Switzerland)2023
Integration of Deep Learning and Sequential Metabolism to Rapidly Screen Dipeptidyl Peptidase (DPP)-IV Inhibitors from
Article in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Techniques for the determination of dipeptidyl peptidase IV and screening of its inhibitors.Journal of pharmaceutical analysis · 2026Review
- Identification and Therapeutic Potential of Polymethoxylated Flavones inMolecules (Basel, Switzerland) · 2025Article
- Digital intelligence technology: new quality productivity for precision traditional Chinese medicine.Frontiers in pharmacology · 2025Review
- Identification, biotransformation, and neuroprotective potential of the ethanol extract ofFrontiers in pharmacology · 2025Article
- Rapid identification of chemical profilesFrontiers in pharmacology · 2024Article
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11 authors.
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Abstract
Traditional Chinese medicine (TCM) possesses unique advantages in the management of blood glucose and lipids. However, there is still a significant gap in the exploration of its pharmacologically active components. Integrated strategies encompassing deep-learning prediction models and active validation based on absorbable ingredients can greatly improve the identification rate and screening efficiency in TCM. In this study, the affinity prediction of 11,549 compounds from the traditional Chinese medicine system's pharmacology database (TCMSP) with dipeptidyl peptidase-IV (DPP-IV) based on a deep-learning model was firstly conducted. With the results,
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