ArticleInternational journal of molecular sciences2024
Targeting Hypoglycemic Natural Products from the Cloud Forest Plants Using Chemotaxonomic Computer-Assisted Selection.
Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Seaweeds From the Veracruz Rocky Shore (Mexico) as Novel Sources of Bioactive Compounds Against Fusarium Species Pathogenic to Corn (Zea mays).Chemistry & biodiversity · 2026Article
- Phytochemical Profile and Bioactive Potential ofCurrent issues in molecular biology · 2026Article
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Authors and funding
7 authors.
Funding
Abstract
The cloud forest (CF), a hugely biodiverse ecosystem, is a hotspot of unexplored plants with potential for discovering pharmacologically active compounds. Without sufficient ethnopharmacological information, developing strategies for rationally selecting plants for experimental studies is crucial. With this goal, a CF metabolites library was created, and a ligand-based virtual screening was conducted to identify molecules with potential hypoglycemic activity. From the most promising botanical families, plants were collected, methanolic extracts were prepared, and hypoglycemic activity was evaluated through in vitro enzyme inhibition assays on α-amylase, α-glucosidase, and dipeptidyl peptidase IV (DPP-IV). Metabolomic analyses were performed to identify the dominant metabolites in the species with the best inhibitory activity profile, and their affinity for the molecular targets was evaluated using ensemble molecular docking. This strategy led to the identification of twelve plants (in four botanical families) with hypoglycemic activity.
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