双(6-氨基-1,3-二甲基嘧啶-2,4(1H,3H)-二酮)作为EGFR抑制剂的硅研究:合成、DFT、分子对接和MD模拟研究

IF 1.6 2区 生物学 Q3 CELL BIOLOGY
Zeynab masoumi, Mohammad Bayat, Davood Gheidari
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引用次数: 0

摘要

表皮生长因子受体(epidermal growth factor receptor, EGFR)是一种位于细胞表面的蛋白,属于酪氨酸激酶家族,在细胞发育和增殖中起着至关重要的作用。EGFR基因的异常表达或突变可导致非小细胞肺癌。虽然已建立的EGFR抑制剂在治疗癌症方面是有效的,但它们与一些副作用有关。因此,迫切需要开发新的EGFR抑制剂,既能有效靶向受体,又不会产生不良副作用。本研究在室温下,不使用任何催化剂,在水中合成了一系列双(6-氨基-1,3-二甲基嘧啶-2,4(1H,3H)-二酮衍生物,并对其药物性能进行了研究。利用密度泛函理论(DFT)、分子对接和分子动力学(MD)等计算方法研究了该分子的化学性质、类药物特性和抗癌潜力。量子化学计算表明,分子相对稳定,并表现出显著的亲电性。对HOMO-LUMO等高线图进行了分析,以说明可能与生物活性相关的电荷密度分布。与EGFR酶的对接研究表明,所有化合物都表现出良好的结合亲和力,对接分数在−4.412至−6.158 kcal/mol之间。其中,化合物3f的结合能为- 6.158 kcal/mol,优于天然配体的- 5.076 kcal/mol。EGFR-3f复合物的稳定性通过在配体-蛋白相互作用中形成5个常规氢键和1个碳氢键而显著增强。对EGFR-3f配合物进行了MD模拟,包括均方根偏差(RMSD)、均方根波动(RMSF)、旋转半径(rGyr)、分子表面积(MolSA)和极性表面积(PSA)等分析。发现EGFR-3f复合物是稳定的,结果表明化合物3f与靶酶有较强的相互作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

In Silico Study of Bis(6-Amino-1,3-Dimethylpyrimidine-2,4(1H,3H)-Diones) as EGFR Inhibitors: Synthesis, DFT, Molecular Docking, and MD Simulation Studies

In Silico Study of Bis(6-Amino-1,3-Dimethylpyrimidine-2,4(1H,3H)-Diones) as EGFR Inhibitors: Synthesis, DFT, Molecular Docking, and MD Simulation Studies

The epidermal growth factor receptor (EGFR), a protein located on the cell surface, belongs to the tyrosine kinase family and plays a crucial role in cell development and proliferation. Abnormal expression or mutations in the EGFR gene can lead to non–small cell lung cancer. Although established EGFR inhibitors have been effective in the treatment of cancer, they are associated with several side effects. As a result, there is an urgent need to develop novel EGFR inhibitors that can effectively target the receptor while causing no adverse side effects. In this study, a series of bis(6-amino-1,3-dimethylpyrimidine-2,4(1H,3H)-dione derivatives was synthesized in water at room temperature without the use of any catalyst, and pharmaceutical properties are investigated. Computational methods, including density functional theory (DFT), molecular docking, and molecular dynamics (MD), were utilized to investigate the chemical properties, drug-like characteristics, and anticancer potential of the molecule. Quantum chemical calculations indicated that the molecules are relatively stable and exhibit significant electrophilic properties. The analysis of HOMO-LUMO contour maps was conducted to illustrate charge density distributions that may be associated with biological activity. Docking studies with EGFR enzymes indicated that all compounds demonstrated favorable binding affinities, with docking scores ranging from −4.412 to −6.158 kcal/mol. Particularly, Compound 3f, with an energy of −6.158 kcal/mol, showed the best binding affinity, outperforming the native ligand, which had a docking score of −5.076 kcal/mol. The stability of the EGFR-3f complex is significantly enhanced by the formation of five conventional hydrogen bonds and one carbon–hydrogen bond in ligand–protein interactions. MD simulations, which included analyses such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (rGyr), molecular surface area (MolSA), and polar surface area (PSA), were conducted on the EGFR-3f complex. It was found that the EGFR-3f complex is stable, and the results show that Compound 3f has a strong interaction with the target enzyme.

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来源期刊
Cellular Microbiology
Cellular Microbiology 生物-微生物学
CiteScore
9.70
自引率
0.00%
发文量
26
审稿时长
3 months
期刊介绍: Cellular Microbiology aims to publish outstanding contributions to the understanding of interactions between microbes, prokaryotes and eukaryotes, and their host in the context of pathogenic or mutualistic relationships, including co-infections and microbiota. We welcome studies on single cells, animals and plants, and encourage the use of model hosts and organoid cultures. Submission on cell and molecular biological aspects of microbes, such as their intracellular organization or the establishment and maintenance of their architecture in relation to virulence and pathogenicity are also encouraged. Contributions must provide mechanistic insights supported by quantitative data obtained through imaging, cellular, biochemical, structural or genetic approaches.
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