ArticleFrontiers in pharmacology2025
Computational-experimental integration identifies potent carbohydrate-hydrolyzing enzyme inhibitors from
Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Viridicatin from the Antarctic FungusAntioxidants (Basel, Switzerland) · 2026Article
- The deformation energy gap in computational drug design: why interaction energy alone cannot rank drug candidates and a thermodynamic correction protocol.Journal of molecular modeling · 2026Article
- Molecular docking, DFT analysis, pharmacokinetic profiling and MD simulation of Ilex aquifolium L. flavonoids as potential α-glucosidase predicted inhibitors for diabetes.Scientific reports · 2026Article
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Authors and funding
5 authors.
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Abstract
Background: Current α-glucosidase and α-amylase inhibitors demonstrate limited therapeutic efficacy and significant gastrointestinal side effects, necessitating identification of novel antidiabetic agents. This study employed integrated computational and experimental approaches to evaluate carbohydrate hydrolyzing enzyme inhibitory potential of Material and methods: Plant extracts were evaluated through enzymatic assays against α-glucosidase and α-amylase. Virtual screening of 144 phytochemicals employed molecular docking, followed by molecular dynamics simulations (100 ns) and density functional theory calculations at B3LYP/6-311++G(d,p) level. ADMET profiling assessed drug-likeness potential. Results: Conclusion:
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