药膏精油抗糖尿病的整体研究:降糖活性、酶抑制、GC-MS表征、ADMET预测、MD模拟和DFT见解

IF 3.1 3区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Ouafa Boudebia, Mohammed Larbi Benamor, Lotfi Bourougaa, Yahia Bekkar, Elhafnaoui Lanez, Aicha Adaika, Rania Bouraoui, Kaouther Nesba, Housseyn Chaoua, Salah Eddine Hachani, Lazhar Bechki, Touhami Lanez
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引用次数: 0

摘要

糖尿病是一种以糖代谢障碍为特征的普遍代谢性疾病。本研究通过体内、体外和计算方法研究了牛膝精油(EO)的抗糖尿病潜能。体外酶抑制实验表明,灰霉病菌EO能有效抑制α-淀粉酶和α-葡萄糖苷酶,提示其在葡萄糖调节中的潜在作用。体内实验进一步证实了其降糖作用。GC-MS分析鉴定出31种生物活性化合物。分子对接研究表明,其中6种化合物与α-淀粉酶和α-葡萄糖苷酶具有较强的结合亲和力,与标准药物阿卡波糖(ARE)的结合亲和力相当。其中,顺式马尾草酯(CVA)和β-松油醇(βTP)对这两种酶的对接得分最高。ADMET分析证实了它们良好的药代动力学性质、药物相似性和低毒性风险。分子动力学模拟表明,CVA和βTP与这两种酶的结合稳定,RMSD和RMSF值低于ARE, Rg和SASA参数也较好。MM-PBSA计算进一步验证了它们的强结合亲和力。密度泛函理论计算更深入地揭示了CVA和βTP的电子特性,揭示了它们的前沿分子轨道分布和能隙(∆E)值。分子静电势分析确定了关键的富电子和缺电子区域,提示了与目标酶的潜在相互作用位点。在水条件下观察到的∆E值降低表明在生理环境下分子稳定性和反应性增加,进一步支持了它们在酶抑制中的作用。总的来说,这项研究强调了C. cinerea EO作为一种有前途的糖尿病治疗天然来源。体内、体外和计算方法的整合为其治疗潜力提供了令人信服的证据。然而,需要进一步的实验验证来评估其临床适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Holistic investigation of Cotula cinerea essential oil against diabetes: hypoglycemic activity, enzymatic inhibition, GC-MS characterization, ADMET forecasting, MD simulations, and DFT insights

Holistic investigation of Cotula cinerea essential oil against diabetes: hypoglycemic activity, enzymatic inhibition, GC-MS characterization, ADMET forecasting, MD simulations, and DFT insights

Holistic investigation of Cotula cinerea essential oil against diabetes: hypoglycemic activity, enzymatic inhibition, GC-MS characterization, ADMET forecasting, MD simulations, and DFT insights

Diabetes mellitus is a prevalent metabolic disorder characterized by impaired glucose metabolism. This study investigates the anti-diabetic potential of Cotula cinerea essential oil (EO) through in vivo, in vitro, and computational methodologies. In vitro enzyme inhibition assays demonstrated that C. cinerea EO effectively inhibits α-amylase and α-glucosidase, indicating its potential role in glucose regulation. In vivo studies further confirmed its hypoglycemic effects. GC–MS analysis identified 31 bioactive compounds within the EO. Molecular docking studies revealed that six of these compounds exhibited strong binding affinities to α-amylase and α-glucosidase, comparable to those of the standard drug acarbose (ARE). Among them, cis-verbenyl acetate (CVA) and β-terpineol (βTP) showed the highest docking scores against both enzymes. ADMET analysis confirmed their favorable pharmacokinetic properties, drug-likeness, and low toxicity risks. Molecular dynamics simulations demonstrated the stable binding of CVA and βTP with both enzymes, exhibiting lower RMSD and RMSF values compared to ARE, along with favorable Rg and SASA parameters. MM-PBSA calculations further validated their strong binding affinities. Density Functional Theory calculations provided deeper insights into the electronic characteristics of CVA and βTP, revealing their frontier molecular orbitals distributions and energy gap (∆E) values. The molecular electrostatic potential analysis identified key electron-rich and electron-deficient regions, suggesting potential interaction sites with the target enzymes. The observed reduction in ∆E values under aqueous conditions indicated increased molecular stability and reactivity within physiological environments, further supporting their role in enzyme inhibition. Overall, this study highlights C. cinerea EO as a promising natural source for diabetes management. The integration of in vivo, in vitro, and computational approaches offers compelling evidence for its therapeutic potential. Nevertheless, further experimental validation is necessary to assess its clinical applicability.

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来源期刊
Journal of Computer-Aided Molecular Design
Journal of Computer-Aided Molecular Design 生物-计算机:跨学科应用
CiteScore
8.00
自引率
8.60%
发文量
56
审稿时长
3 months
期刊介绍: The Journal of Computer-Aided Molecular Design provides a form for disseminating information on both the theory and the application of computer-based methods in the analysis and design of molecules. The scope of the journal encompasses papers which report new and original research and applications in the following areas: - theoretical chemistry; - computational chemistry; - computer and molecular graphics; - molecular modeling; - protein engineering; - drug design; - expert systems; - general structure-property relationships; - molecular dynamics; - chemical database development and usage.
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