LC-MS profiling and multi-target mechanistic insights of Hibiscus rosa-sinensis in diabetes: Network pharmacology, molecular docking, MD simulation, PCA, and in-vitro α-amylase inhibition

Shankar Thapa , Sharvendra Nath Maurya , Kavya Manjunath , Ammar A․Razzak Mahmood , Kalpana Devi , Shithin Ann Varghese , Ashish Lamsal , Binaya Tamang , Mahalakshmi Suresha Biradar
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引用次数: 0

Abstract

Background

Hibiscus rosa-sinensis Linn. (Zhū Jǐn Huā), known in Traditional Chinese Medicine (TCM) as Dà Hóng Huā, has been widely used for its cooling, detoxifying, and anti-inflammatory properties. It is a medicinal plant traditionally used for managing diabetes, yet its multi-target mechanisms remain largely unexplored. This study aimed to investigate the anti-diabetic potential of H. rosa-sinensis through LC-MS-based phytochemical profiling, network pharmacology, molecular docking, molecular dynamics (MD) simulations, principal component analysis (PCA), and in vitro α-amylase inhibition assay.

Methods

LC-MS analysis was performed to identify bioactive compounds present in the methanolic extract of H. rosa-sinensis. Identified compounds were subjected to network pharmacology analysis to predict potential diabetes-related protein targets. Key compound-target interactions were evaluated using molecular docking (AutoDock Vina v1.2.0), followed by 100 ns MD simulations to assess structural stability and binding dynamics. PCA and free energy landscape (FEL) analyses were conducted to examine conformational behaviour. Finally, in vitro α-amylase inhibition was tested to validate the hypoglycaemic potential.

Results

Quercetin demonstrated strong binding affinities with PTK2 (–8.2 kcal/mol), SRC (–9.2 kcal/mol), and α-amylase (–8.9 kcal/mol), suggesting its multi-target action in diabetes. MD simulation confirmed the structural stability of all three complexes over 100 ns, supported by consistent RMSD and favourable interaction profiles. The PCA and FEL analyses showed minimal conformational fluctuations and energetically favourable states. The in vitro α-amylase inhibition assay further validated the antidiabetic potential, with an IC50 value of 107.75 µg/mL for the H. rosa-sinensis flower extract.

Conclusion

This integrative study provides strong evidence for the multi-target antidiabetic potential of Hibiscus rosa-sinensis, primarily attributed to quercetin and its derivatives. The findings highlight stable interactions with key diabetic targets and demonstrate significant α-amylase inhibition, supporting the traditional use of H. rosa-sinensis as a complementary therapy for diabetes management.
木槿花在糖尿病中的LC-MS分析和多靶点机制:网络药理学、分子对接、MD模拟、PCA和体外α-淀粉酶抑制
背景:芙蓉。(zhj ā Jǐn花ā),在中医(TCM)中被称为d Hóng花ā,因其冷却,排毒和抗炎特性而被广泛使用。它是一种传统上用于治疗糖尿病的药用植物,但其多靶点机制在很大程度上仍未被探索。本研究旨在通过lc - ms植物化学分析、网络药理学、分子对接、分子动力学(MD)模拟、主成分分析(PCA)和体外α-淀粉酶抑制实验等方法,探讨红荆的抗糖尿病潜能。方法采用高效液相色谱-质谱法(slc - ms)对红桃醇提物中的活性成分进行鉴定。对鉴定出的化合物进行网络药理学分析,以预测潜在的糖尿病相关蛋白靶点。通过分子对接(AutoDock v1.2.0)评估关键化合物-靶标相互作用,然后进行100 ns MD模拟以评估结构稳定性和结合动力学。采用主成分分析和自由能景观(FEL)分析来考察构象行为。最后,体外α-淀粉酶抑制实验验证了其降糖潜能。结果squercetin与PTK2 (-8.2 kcal/mol)、SRC (-9.2 kcal/mol)和α-淀粉酶(-8.9 kcal/mol)具有较强的结合亲和力,提示其在糖尿病中的多靶点作用。MD模拟证实了这三种配合物在100 ns内的结构稳定性,并得到了一致的RMSD和良好的相互作用曲线的支持。主成分分析和FEL分析显示最小的构象波动和能量有利状态。体外α-淀粉酶抑制实验进一步验证了红花提取物的抗糖尿病作用,其IC50值为107.75µg/mL。结论木槿具有多靶点的降糖作用,槲皮素及其衍生物可能是其主要作用机制。该研究结果强调了与糖尿病关键靶点的稳定相互作用,并显示出显著的α-淀粉酶抑制作用,支持了红木作为糖尿病治疗的补充疗法的传统应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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