ArticleNutrients2023
Construction of a QSAR Model Based on Flavonoids and Screening of Natural Pancreatic Lipase Inhibitors.
Article in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Preliminary In Vitro Screening of Structure-Dependent β-Hydroxybutyrate Responses to Dietary Fatty Acids in Hepatocyte Models.Nutrients · 2026Article
- Integrating QSAR-Machine Learning, Biochemical Assays, and Molecular Dynamics for the Discovery of JAK2 Inhibitors in Cervical Cancer.Journal of chemical information and modeling · 2026Article
- Natural Products in Epilepsy Treatment: From Traditional Medicine Towards Computational Drug Discovery.Current issues in molecular biology · 2026Review
- Leveraging Natural Compounds for Pancreatic Lipase Inhibition via Virtual Screening.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Rosemarinic Acid-Induced Destabilization of Aβ Peptides: Insights from Molecular Dynamics Simulations.Foods (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
Pancreatic lipase (PL) is a key hydrolase in lipid metabolism. Inhibition of PL activity can intervene in obesity, a global sub-health disease. The natural product is considered a good alternative to chemically synthesized drugs due to its advantages, such as low side effects. However, traditional experimental screening methods are labor-intensive and cost-consuming, and there is an urgent need to develop high-throughput screening methods for the discovery of anti-PL natural products. In this study, a high-throughput virtual screening process for anti-PL natural products is provided. Firstly, a predictable anti-PL natural product QSAR model (R
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.