Evidence map›Paper›PMID 37571426›Full record

ArticleNutrients2023

Construction of a QSAR Model Based on Flavonoids and Screening of Natural Pancreatic Lipase Inhibitors.

Yutong Yuan, Fei Pan, Zehui Zhu, Zichen Yang, Ou Wang, Qing Li, Liang Zhao, Lei Zhao

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.4field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Yutong YuanBeijing Engineering and Technology Research Center of Food Additives, School of Food and Health, Beijing Technology and Business University, Beijing 100048, China.
Fei PanInstitute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing 100093, China.ORCID 0000-0001-9898-1238
Zehui ZhuBeijing Engineering and Technology Research Center of Food Additives, School of Food and Health, Beijing Technology and Business University, Beijing 100048, China.
Zichen YangBeijing Engineering and Technology Research Center of Food Additives, School of Food and Health, Beijing Technology and Business University, Beijing 100048, China.
Ou WangNational Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Qing LiBeijing Engineering and Technology Research Center of Food Additives, School of Food and Health, Beijing Technology and Business University, Beijing 100048, China.
Liang ZhaoBeijing Engineering and Technology Research Center of Food Additives, School of Food and Health, Beijing Technology and Business University, Beijing 100048, China.ORCID 0000-0003-2542-9279
Lei ZhaoBeijing Engineering and Technology Research Center of Food Additives, School of Food and Health, Beijing Technology and Business University, Beijing 100048, China.
Beijing Technology and Business University · CNChinese Academy of Agricultural Sciences · CNChinese Center For Disease Control and Prevention · CN

Funding

Beijing Technology and Business University Beijing Technology and Business UniversityBeijing Technology and Business University No. QNJJ2022-06Beijing Technology and Business University No. SPKX-202204National Health Commission of the People's Republic of China No. wlkfz202205
6 · The paper itself

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

Indexed as

Biological ProductsLipaseArtificial IntelligenceEnzyme InhibitorsFlavonoidsMolecular Docking SimulationPancreatic HormonesQuantitative Structure-Activity RelationshipBiological ProductsEnzyme InhibitorsFlavonoidsLipasePancreatic Hormonesdietary flavonoidsmolecular mechanics/generalized born surface areamolecular simulationpancreatic lipasequantitative structure-activity relationship

Identifiers

PMID37571426
PMCPMC10421515
OpenAlexW4385630482

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.