ArticlePloS one2023
In Silico identification of novel phytochemicals that target SFRP4: An early biomarker of diabesity.
Article in PloS one, 2023. 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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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
2 citing papers in PubMed, 8 citations in OpenAlex.
- Article
- Plasma sFRP4 Levels and Their Relationship with HOMA IR in Women with Gestational Diabetes Mellitus.Medical journal of the Islamic Republic of Iran · 2025Article
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Authors and funding
5 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
The simultaneous coexistence of complicated metabolic conditions like obesity and diabetes within an individual is known as diabesity. Obesity is the key factor for many chronic diseases, including insulin resistance and type 2 diabetes (T2D). Metabolic stress due to nutrient overload releases different inflammatory mediators. Secreted frizzled-related protein 4 (SFRP4) is also an inflammatory mediator that impairs insulin secretion. SFRP4 acts as an early biomarker for diabesity expressed with interleukin-1 beta (IL-1β) in the adipose tissues that hinder the exocytosis of insulin-secreting granules from the pancreatic β-cells and is a potential target for preserving β-cell dysfunction and the diabesity treatment. The current study aimed to screen potential bioactive compounds targeting and inhibiting the diabesity-linked SFRP4 protein through an in silico approach. The three-dimensional (3D) structure of human SFRP4 was predicted through comparative modeling techniques and evaluated by various online bioinformatics tools. The molecular docking and MD simulation investigations were carried out against phytochemicals with anti-diabetic and anti-obesity properties to shortlist the best SFRP4 inhibitor. Hesperetin, Curcumin, Isorhamnetin, Embelin, Epicatechin, and Methyl Eugenol interacted strongly with SFRP4 by displaying zero RMSD and binding affinities of -6.5, -6.4, -6.3, -5.3, -6.3 and -5.8 kcal/mol respectively. Additionally, the root mean square fluctuation and root mean square deviation graphs from the MD simulation results demonstrated that hesperetin has good variations throughout the simulation period as compared to others. This dynamic stability and control behavior of hesperetin, when it interacts with SFRP4, shows that it has the potential to modulate the function and activity of the protein. Therefore, hesperetin is identified as an effective and top drug candidate through this analysis for preserving beta-cell function and treating diabesity by targeting SFRP4. The findings of this study could be useful in the design and development of diabesity drugs.
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