Sharma Sachin, Choudhary Manjusha, Sharma Onkar, Injeti Elisha, Mittal Ashwani
Institute of Pharmaceutical Sciences, Kurukshetra University, Kurukshetra 136119, India.
Skeletal Muscle Lab, IIHS, Kurukshetra University, Kurukshetra, Haryana 136119, India.
Comput Biol Chem. 2024 Dec;113:108185. doi: 10.1016/j.compbiolchem.2024.108185. Epub 2024 Aug 28.
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 (∆G) 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 ∆G 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.
垂叶榕传统上用于治疗糖尿病，其提取物可抑制碳水化合物/脂质代谢并具有抗高血糖潜力。然而，关于垂叶榕提取物对碳水化合物代谢的影响存在相互矛盾的研究。因此，其抗糖尿病潜力背后的生物活性和作用机制仍然缺乏。本研究通过鉴定潜在的植物成分和作用机制来探索垂叶榕的抗糖尿病特性。采用了一种顺序性的计算机模拟方法，即类药性、分子对接、对接后MM-GBSA、ADMET研究、分子动力学模拟（MDS）和MDS后MM-GBSA。我们筛选了约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，即胰岛素受体（IR）、二肽基肽酶-4（DPP-4）、过氧化物酶体增殖物激活受体γ（ppar-γ）、过氧化物酶体增殖物激活受体α（ppar-α）、过氧化物酶体增殖物激活受体δ（ppar-δ）、胰高血糖素样肽-1受体（GLP-1R）、沉默信息调节因子1（SIRT-1）、腺苷酸活化蛋白激酶（AMPK）、糖原合成酶激酶-3β（GSK-3β）、晚期糖基化终末产物受体（RAGE）和醛糖还原酶（AR））。类药性研究在32种植物成分中鉴定出18种可成药的候选物。以IR作为标准靶点，从可成药配体中鉴定出K3A、槲皮素、黄芩素、山梨酚苷和沃吉灵J为潜在配体。随后，潜在配体与其余的O.S.D.Ts进行对接，数据显示K3A与AMPK、ppar-δ、DPP-4和GSK-3β强烈结合，而黄芩素与AR和ppar-α结合。山梨酚苷、槲皮素和沃吉灵J分别与ppar-α、ppar-γ和RAGE结合。对接后MM-GBSA数据（∆G）也显示了潜在配体与其相应靶点的强结合亲和力。此后，模拟数据显示只有黄芩素和山梨酚苷分别与其各自的靶点即AR/ppar-α和ppar-α表现出动态稳定性。有趣的是，MDS后MM-GBSA显示只有黄芩素与AR和ppar-α分别表现出-55.08 kcal/mol和-75.48 kcal/mol的强∆G。尽管如此，综合计算分析支持垂叶榕通过黄芩素对AR和ppar-α的调节具有抗糖尿病潜力。
