Exploring the anti-gout potential of sunflower receptacles alkaloids: A computational and pharmacological analysis

Wang, Kaiyu; Cui, Huizi; Liu, Kaifeng; He, Qizheng; Fu, Xueqi; Li, Wannan; Han, Weiwei

doi:10.1016/j.compbiomed.2024.108252

Cited by 6 publications

(2 citation statements)

References 49 publications

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“…Post-MD simulation, trajectory analysis was conducted. As shown in Figure 5, the Root Mean Square Deviation (RMSD) revealed the deviation of the complex from its initial conformation [24,25]. Fluctuations in RMSD indicated conformational changes during the simulation.…”

Section: Peptides Screening Based On Structurementioning

confidence: 95%

Integrating Computational and Experimental Methods to Identify Novel Sweet Peptides from Egg and Soy Proteins

Su,

Liu,

Cui

et al. 2024

IJMS

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Sweetness in food delivers a delightful sensory experience, underscoring the crucial role of sweeteners in the food industry. However, the widespread use of sweeteners has sparked health concerns. This underscores the importance of developing and screening natural, health-conscious sweeteners. Our study represents a groundbreaking venture into the discovery of such sweeteners derived from egg and soy proteins. Employing virtual hydrolysis as a novel technique, our research entailed a comprehensive screening process that evaluated biological activity, solubility, and toxicity of the derived compounds. We harnessed cutting-edge machine learning methodologies, specifically the latest graph neural network models, for predicting the sweetness of molecules. Subsequent refinements were made through molecular docking screenings and molecular dynamics simulations. This meticulous research approach culminated in the identification of three promising sweet peptides: DCY(Asp-Cys-Tyr), GGR(Gly-Gly-Arg), and IGR(Ile-Gly-Arg). Their binding affinity with T1R2/T1R3 was lower than −15 kcal/mol. Using an electronic tongue, we verified the taste profiles of these peptides, with IGR emerging as the most favorable in terms of taste with a sweetness value of 19.29 and bitterness value of 1.71. This study not only reveals the potential of these natural peptides as healthier alternatives to traditional sweeteners in food applications but also demonstrates the successful synergy of computational predictions and experimental validations in the realm of flavor science.

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Section: Peptides Screening Based On Structurementioning

confidence: 95%

Integrating Computational and Experimental Methods to Identify Novel Sweet Peptides from Egg and Soy Proteins

Su,

Liu,

Cui

et al. 2024

IJMS

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this study, we employed network pharmacology and cellular assays to probe the intricate interactions by which the primary bioactive constituents of Baikal skullcap might mitigate T2DM. We utilized LC-MS and the TCMSP database [20] to identify and screen for effective active small molecules in Baikal skullcap, upon which we conducted cluster analysis [21]. We have identified six flavonoid molecules that exhibit potential for pharmaceutical development due to their dual function in inhibiting the PTP1B enzyme and manifesting anti-inflammatory effects.…”

Section: Introductionmentioning

confidence: 99%

Unveiling Anti-Diabetic Potential of Baicalin and Baicalein from Baikal Skullcap: LC–MS, In Silico, and In Vitro Studies

Zhao,

Cui,

Liu

et al. 2024

IJMS

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Type 2 diabetes mellitus (T2DM) is marked by persistent hyperglycemia, insulin resistance, and pancreatic β-cell dysfunction, imposing substantial health burdens and elevating the risk of systemic complications and cardiovascular diseases. While the pathogenesis of diabetes remains elusive, a cyclical relationship between insulin resistance and inflammation is acknowledged, wherein inflammation exacerbates insulin resistance, perpetuating a deleterious cycle. Consequently, anti-inflammatory interventions offer a therapeutic avenue for T2DM management. In this study, a herb called Baikal skullcap, renowned for its repertoire of bioactive compounds with anti-inflammatory potential, is posited as a promising source for novel T2DM therapeutic strategies. Our study probed the anti-diabetic properties of compounds from Baikal skullcap via network pharmacology, molecular docking, and cellular assays, concentrating on their dual modulatory effects on diabetes through Protein Tyrosine Phosphatase 1B (PTP1B) enzyme inhibition and anti-inflammatory actions. We identified the major compounds in Baikal skullcap using liquid chromatography–mass spectrometry (LC–MS), highlighting six flavonoids, including the well-studied baicalein, as potent inhibitors of PTP1B. Furthermore, cellular experiments revealed that baicalin and baicalein exhibited enhanced anti-inflammatory responses compared to the active constituents of licorice, a known anti-inflammatory agent in TCM. Our findings confirmed that baicalin and baicalein mitigate diabetes via two distinct pathways: PTP1B inhibition and anti-inflammatory effects. Additionally, we have identified six flavonoid molecules with substantial potential for drug development, thereby augmenting the T2DM pharmacotherapeutic arsenal and promoting the integration of herb-derived treatments into modern pharmacology.

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Dissecting molecular mechanisms underlying the inhibition of β-glucuronidase by alkaloids from Hibiscus trionum: Integrating in vitro and in silico perspectives

Kamel,

Alkhayl,

Alqhtani

et al. 2024

Computers in Biology and Medicine

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Exploring the anti-gout potential of sunflower receptacles alkaloids: A computational and pharmacological analysis

Cited by 6 publications

References 49 publications

Integrating Computational and Experimental Methods to Identify Novel Sweet Peptides from Egg and Soy Proteins

Integrating Computational and Experimental Methods to Identify Novel Sweet Peptides from Egg and Soy Proteins

Unveiling Anti-Diabetic Potential of Baicalin and Baicalein from Baikal Skullcap: LC–MS, In Silico, and In Vitro Studies

Dissecting molecular mechanisms underlying the inhibition of β-glucuronidase by alkaloids from Hibiscus trionum: Integrating in vitro and in silico perspectives

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