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预测蛋白质-药物相互作用、药效基团建模以及新型 2 型糖尿病治疗药物的毒代动力学。

Prediction of Protein-Drug Interactions, Pharmacophore Modeling, and Toxicokinetics of Novel Leads for Type 2 Diabetes Treatment.

机构信息

Department of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Lovely Professional University, Jalandhar-Delhi G.T. Road (NH-1), Phagwara (Punjab), 144411, India.

出版信息

Curr Drug Metab. 2024;25(5):355-380. doi: 10.2174/0113892002321919240801065905.

DOI:10.2174/0113892002321919240801065905
PMID:39108115
Abstract

BACKGROUND

Small heterocyclic compounds have been crucial in pioneering advances in type 2 diabetes treatment. There has been a dramatic increase in the pharmacological development of novel heterocyclic derivatives aimed at stimulating the activation of Glucokinase (GK). A pharmaceutical intervention for diabetes is increasingly targeting GK as a legitimate target. Diabetes type 2 compromises Glucokinase's function, an enzyme vital for maintaining the balance of blood glucose levels. Medicinal substances strategically positioned to improve type 2 diabetes management are used to stimulate the GK enzyme using heterocyclic derivatives.

OBJECTIVE

The research endeavor aimed to craft novel compounds, drawing inspiration from the inherent coumarin nucleus found in nature. The goal was to evoke the activity of the glucokinase enzyme, offering a tailored approach to mitigate the undesired side effects typically associated with conventional therapies employed in the treatment of type 2 diabetes.

METHODS

Coumarin, sourced from nature's embrace, unfolds as a potent and naturally derived ally in the quest for innovative antidiabetic interventions. Coumarin was extracted from a variety of botanical origins, including Artemisia keiskeana, Mallotus resinosus, Jatropha integerrima, Ferula tingitana, Zanthoxylum schinifolium, Phebalium clavatum, and Mammea siamensis. This inclusive evaluation was conducted on Muybridge's digital database containing 53,000 hit compounds. The presence of the coumarin nucleus was found in 100 compounds, that were selected from this extensive repository. Utilizing Auto Dock Vina 1.5.6 and ChemBioDraw Ultra, structures generated through this process underwent docking analysis. Furthermore, these compounds were accurately predicted online log P using the Swiss ADME algorithm. A predictive analysis was conducted using PKCSM software on the primary compounds to assess potential toxicity.

RESULTS

Using Auto Dock Vina 1.5.6, 100 coumarin derivatives were assessed for docking. Glucokinase (GK) binding was significantly enhanced by most of these compounds. Based on superior binding characteristics compared with Dorzagliatin (standard GKA) and MRK (co-crystallized ligand), the top eight molecules were identified. After further evaluation through ADMET analysis of these eight promising candidates, it was confirmed that they met the Lipinski rule of five and their pharmacokinetic profile was enhanced. The highest binding affinity was demonstrated by APV16 at -10.6 kcal/mol. A comparison between the APV16, Dorzagliatin and MRK in terms of toxicity predictions using PKCSM indicated that the former exhibited less skin sensitization, AMES toxicity, and hepatotoxicity.

CONCLUSION

Glucokinase is most potently activated by 100 of the compound leads in the database of 53,000 compounds that contain the coumarin nucleus. APV12, with its high binding affinity, favorable ADMET (adjusted drug metabolic equivalents), minimal toxicity, and favorable pharmacokinetic profile warrants consideration for progress to in vitro testing. Nevertheless, to uncover potential therapeutic implications, particularly in the context of type 2 diabetes, thorough investigations and in-vivo evaluations are necessary for benchmarking before therapeutic use, especially experiments involving the STZ diabetic rat model.

摘要

背景

小杂环化合物在 2 型糖尿病治疗的开创性进展中发挥了至关重要的作用。新型杂环衍生物的药理学开发急剧增加,旨在刺激葡萄糖激酶(GK)的激活。针对糖尿病的药物干预越来越将 GK 作为一个合法的靶点。2 型糖尿病削弱了葡萄糖激酶的功能,葡萄糖激酶是维持血糖水平平衡的关键酶。用于改善 2 型糖尿病管理的药物物质被战略性地定位为使用杂环衍生物刺激 GK 酶。

目的

研究旨在设计新型化合物,灵感来自自然界中固有的香豆素核。目标是唤起葡萄糖激酶酶的活性,提供一种针对传统疗法治疗 2 型糖尿病的不良副作用的定制方法。

方法

香豆素是从自然界中提取的一种强大的天然衍生物质,是探索创新抗糖尿病干预措施的有力盟友。香豆素从多种植物来源中提取,包括青蒿、乳香、麻疯树、地椒、花椒、杠柳、和暹罗马钱子。在包含 53000 个命中化合物的 Muybridge 数字数据库上进行了这种综合评估。在 100 种化合物中发现了香豆素核,这些化合物是从这个广泛的存储库中选择的。利用 Auto Dock Vina 1.5.6 和 ChemBioDraw Ultra,通过该过程生成的结构进行了对接分析。此外,这些化合物的准确预测在线使用瑞士 ADME 算法计算 log P。使用 PKCSM 软件对主要化合物进行预测性分析,以评估潜在的毒性。

结果

使用 Auto Dock Vina 1.5.6 对 100 种香豆素衍生物进行了对接评估。大多数这些化合物显著增强了葡萄糖激酶(GK)的结合。与 Dorzagliatin(标准 GKA)和 MRK(共结晶配体)相比,基于优越的结合特性,确定了前 8 种分子。对这 8 种有前途的候选化合物进行 ADMET 分析进一步评估后,证实它们符合 Lipinski 五规则,并且改善了它们的药代动力学特征。APV16 的最高结合亲和力为-10.6 kcal/mol。使用 PKCSM 对 APV16、Dorzagliatin 和 MRK 在毒性预测方面进行比较表明,前者表现出较少的皮肤致敏性、AMES 毒性和肝毒性。

结论

在包含香豆素核的 53000 种化合物的数据库中,100 种化合物先导中的葡萄糖激酶最有效地被激活。APV12 具有高结合亲和力、良好的 ADMET(调整后的药物代谢当量)、最小的毒性和良好的药代动力学特征,值得考虑进行体外测试。然而,为了揭示潜在的治疗意义,特别是在 2 型糖尿病的背景下,在进行治疗用途之前,需要进行全面的调查和体内评估,特别是涉及 STZ 糖尿病大鼠模型的实验。

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