薜荔维仁针对多器官特异性糖尿病靶点的抗糖尿病潜力的机理研究:分子对接、MDS、MM-GBSA 分析

IF 2.6 4区 生物学 Q2 BIOLOGY Computational Biology and Chemistry Pub Date : 2024-08-28 DOI:10.1016/j.compbiolchem.2024.108185
Sachin Sharma , Manjusha Choudhary , Onkar Sharma , Elisha Injeti , Ashwani Mittal
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引用次数: 0

摘要

薜荔历来被用于治疗糖尿病,其提取物可抑制碳水化合物/脂质代谢,具有抗高血糖的潜力。然而,关于薜荔提取物对碳水化合物代谢的影响,目前还存在相互矛盾的研究。因此,有关其抗糖尿病潜力背后的生物活性和机制的研究仍然很少。本研究通过鉴定潜在的植物成分和机制来探索 F. viren 的抗糖尿病特性。本研究采用了一种连续的硅学方法,即药物相似性、分子对接、对接后 MM-GBSA、ADMET 研究、分子动态模拟(MDS)和分子动态模拟后 MM-GBSA。我们筛选了 32 种植物成分和 12 个潜在的器官特异性糖尿病靶点(O.S.D.Ts,即 IR、DPP-4、ppar-γ、ppar-α、ppar-δ、GLP-1R、SIRT-1、AMPK、GSK-3β、RAGE 和 AR)。药物相似性研究在 32 种植物成分中发现了 18 种候选药物。以红外光谱为标准靶标,从可药用配体中鉴定出 K3A、槲皮素、黄芩苷、山梨糖醇和伏格列林为潜在配体。随后,潜在配体与剩余的 O.S.D.Ts. 进行了对接,数据显示 K3A 与 AMPK、par-δ、DPP-4 和 GSK-3β 有很强的结合力,而黄芩苷则与 AR 和 ppar-α 有很强的结合力。山梨醇、槲皮素和伏桂林 J 分别与 ppar-α、ppar-γ 和 RAGE 结合。对接后的 MM-GBSA 数据(ΔGBind)也显示了潜在配体与相应靶点的强结合亲和力。之后的模拟数据显示,只有黄芩苷和山嵛素与各自的靶标(即 AR/ppar-α 和 ppar-α)分别表现出动态稳定性。有趣的是,后 MDS MM-GBSA 发现,只有黄芩苷与 AR 和 ppar-α 的∆GBind 分别为 -55.08 kcal/mol 和 -75.48 kcal/mol。尽管如此,通过黄芩苷对 AR 和 ppar-α 的调节,集体计算分析支持了 F. viren 的抗糖尿病潜力。
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Mechanistic insights into antidiabetic potential of Ficus viren against multi organ specific diabetic targets: molecular docking, MDS, MM-GBSA analysis

Ficus viren has been traditionally used to treat diabetes, and its extract inhibits carbohydrate/lipid metabolism and possesses anti-hyperglycemic potential. However, there is conflicting investigation related to F. viren extract effect on carbohydrate metabolism. Thus, bioactive and mechanism behind its antidiabetic potential is still scanty. This study explored F. viren’s anti-diabetic property by identifying potential phytoconstituents and mechanism. A sequential in-silico approach was used i.e., druglikeness, molecular docking, post-docking MM-GBSA, ADMET studies, molecular dynamic simulation (MDS), and post-MDS MM-GBSA. We screened ∼32 phytoconstituents and twelve potential organ-specific diabetic targets (O.S.D.Ts i.e., IR, DPP-4, ppar-γ, ppar-α, ppar-δ, GLP-1R, SIRT-1, AMPK, GSK-3β, RAGE, and AR). Drug likeness study identified 18 druggable candidates among 32 phytoconstituents. K3A, quercetin, scutellarein, sorbifolin, and vogeline J identified as potential ligands from druggable ligands, using IR as the standard target. Subsequently, potential ligands docked with remaining O.S.D.Ts. and data showed that K3A binds strongly with AMPK, ppar-δ, DPP-4, and GSK-3β, while scutellarein binds with AR and ppar-α. Sorbifolin, quercetin, and vogeline J binds with ppar-α, ppar-γ, and RAGE, respectively. Post-docking MM-GBSA data (∆GBind) also depicted potential ligand’s strong binding affinities with their corresponding targets. Thereafter, simulation data revealed that only scutellarein and sorbifolin showed dynamic stability with their respective targets, i.e., AR/ppar-α and ppar-α, respectively. Interestingly, post-MDS MM-GBSA revealed that only scutellarein exhibited strong ∆GBind of −55.08 kcal/mol and −75.48 kcal/mol with AR and ppar-α, respectively. Though, collective computational analysis supports antidiabetic potential of F. viren through AR and ppar-α modulation by scutellarein.

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来源期刊
Computational Biology and Chemistry
Computational Biology and Chemistry 生物-计算机:跨学科应用
CiteScore
6.10
自引率
3.20%
发文量
142
审稿时长
24 days
期刊介绍: Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered. Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered. Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.
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