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假木豆化学成分针对抗糖尿病靶点的虚拟筛选、ADME预测、类药性及分子对接分析

Virtual screening, ADME prediction, drug-likeness, and molecular docking analysis of Fagonia indica chemical constituents against antidiabetic targets.

作者信息

Riaz Rabia, Parveen Shagufta, Shafiq Nusrat, Ali Awais, Rashid Maryam

机构信息

Synthetic & Natural Product Discovery Lab, Department of Chemistry, Government College Women University, Faisalabad, 38000, Pakistan.

Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, 2300, Pakistan.

出版信息

Mol Divers. 2025 Apr;29(2):1139-1160. doi: 10.1007/s11030-024-10897-7. Epub 2024 Jul 16.

Abstract

Fagonia indica from Zygophyllaceae family is a medicinal specie with significant antidiabetic potential. The present study aimed to investigate the in vitro antidiabetic activity of Fagonia indica crude extract followed by an in silico screening of its phytoconstituents. For this purpose, crude extract of Fagonia indica was prepared and divided in three different parts, i.e., n-hexane, ethyl acetate, and methanolic fraction. Based on in vitro outcomes, the phytochemical substances of Fagonia indica were virtually screened through a literature survey and a screening library of compounds (1-13) was prepared. The clinical potential of these novel drug candidates was assessed by applying an ADME screening profile. Findings of SwissADME indicators (Absorption, Distribution, Metabolism, and Excretion) for the compounds (1-13) presented relatively optimal physicochemical characteristics, drug-likeness, and medicinal chemistry. The antidiabetic action of these leading drug candidates was optimized through molecular docking analysis against 3 different human pancreatic α-amylase macromolecular targets with (PDB ID 1B2Y), (PDB ID 3BAJ), and (PDB ID: 3OLI) by applying Virtual Docker (Molegro MVD). Metformin was taken as a reference standard for the sake of comparison. In vitro antidiabetic evaluation gave good results with promising α-amylase inhibitory action in the form of IC values, as for n-hexane extract = 206.3 µM, ethyl acetate = 41.64 µM, and methanolic extract = 9.61 µM. According to in silico outcomes, all 13 phytoconstituents possess the best binding affinity with successful MolDock scores ranging from - 97.2003 to - 65.6877 kcal/mol and show a great number of binding interactions than native drug metformin. Therefore, the current work concluded that the diabetic inhibition prospective of extract and the compounds of Fagonia indica may contribute to being investigated as a new class of antidiabetic drug or drug-like candidate for further studies.

摘要

蒺藜科的印度刺山柑是一种具有显著抗糖尿病潜力的药用植物。本研究旨在研究印度刺山柑粗提物的体外抗糖尿病活性,并对其植物成分进行计算机模拟筛选。为此,制备了印度刺山柑粗提物,并将其分为三个不同部分,即正己烷、乙酸乙酯和甲醇部分。根据体外实验结果,通过文献调研对印度刺山柑的植物化学物质进行了虚拟筛选,并制备了化合物(1 - 13)的筛选库。通过应用ADME筛选图谱评估了这些新型候选药物的临床潜力。化合物(1 - 13)的瑞士ADME指标(吸收、分布、代谢和排泄)结果显示出相对优化的物理化学特性、类药性和药物化学性质。通过应用虚拟对接软件(Molegro MVD),针对3种不同的人类胰腺α -淀粉酶大分子靶点(PDB ID 1B2Y)、(PDB ID 3BAJ)和(PDB ID: 3OLI)进行分子对接分析,优化了这些主要候选药物的抗糖尿病作用。以二甲双胍作为参考标准进行比较。体外抗糖尿病评估取得了良好结果,以IC值表示,具有有前景的α -淀粉酶抑制作用,正己烷提取物的IC值为2​​06.3 μM,乙酸乙酯提取物为41.64 μM,甲醇提取物为9.61 μM。根据计算机模拟结果,所有13种植物成分都具有最佳结合亲和力,成功的MolDock分数范围为 - 97.2003至 - 65.6877 kcal/mol,并且与天然药物二甲双胍相比显示出大量的结合相互作用。因此,当前研究得出结论,印度刺山柑提取物和化合物的糖尿病抑制前景可能有助于作为一类新型抗糖尿病药物或类药物候选物进行进一步研究。

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