ArticleFoods (Basel, Switzerland)2022
Construction of an MLR-QSAR Model Based on Dietary Flavonoids and Screening of Natural α-Glucosidase Inhibitors.
Article in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Research progress on the metabolic fate of citrus flavonoids and strategies to improve bioavailability.Food chemistry: X · 2026Review
- Preliminary In Vitro Screening of Structure-Dependent β-Hydroxybutyrate Responses to Dietary Fatty Acids in Hepatocyte Models.Nutrients · 2026Article
- Unraveling the Antimelanogenic Potential ofJournal of agricultural and food chemistry · 2026Article
- Integrating Network Pharmacology and Experimental Validation to Elucidate the Role of Huaier in Attenuating Liver Fibrosis via the AKT Signalling Pathway.Clinical and experimental medicine · 2026Article
- Anti-inflammatory effects of 3PO in asthmatic airway inflammation: an integrated study using network pharmacology, molecular modelling, andFrontiers in pharmacology · 2026Article
- Article
- Identification of Antioxidant Methyl Derivatives ofInternational journal of molecular sciences · 2024Article
- Probing the binding mechanism of tea polyphenols from different processing methods to anti-obesity and TMAO production-related enzymes throughFood chemistry: X · 2024Article
- Optimizing ChEMBL-derived QSAR models for natural flavonoid screening: chemotype-specific predictive reliability in α-glucosidase-inhibition.Drug target insightsArticle
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Authors and funding
9 authors.
Funding
Abstract
Postprandial hyperglycemia can be reduced by inhibiting α-glucosidase activity. Common α-glucosidase inhibitors such as acarbose may have various side effects. Therefore, it is important to find natural products that are non-toxic and have high α-glucosidase-inhibitory activity. In the present study, a comprehensive computational analysis of 27 dietary flavonoid compounds with α-glucosidase-inhibitory activity was performed. These included flavonoids, flavanones, isoflavonoids, dihydrochalcone, flavan-3-ols, and anthocyanins. Firstly, molecular fingerprint similarity clustering analysis was performed on the target molecules. Secondly, multiple linear regression quantitative structure-activity relationship (MLR-QSAR) models of dietary flavonoids (2D descriptors and 3D descriptors optimized), with R
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