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运用计算机模拟方法研究黄酮类化合物库作为癌症治疗靶点 MEK2 的潜在抑制剂。

Investigating a Library of Flavonoids as Potential Inhibitors of a Cancer Therapeutic Target MEK2 Using in Silico Methods.

机构信息

Department of Biochemistry, Faculty of Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia.

Special Infectious Agents Unit-BSL3, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia.

出版信息

Int J Mol Sci. 2023 Feb 23;24(5):4446. doi: 10.3390/ijms24054446.

Abstract

The second leading cause of death in the world is cancer. Mitogen-activated protein kinase (MAPK) and extracellular signal-regulated protein kinase (ERK) 1 and 2 (MEK1/2) stand out among the different anticancer therapeutic targets. Many MEK1/2 inhibitors are approved and widely used as anticancer drugs. The class of natural compounds known as flavonoids is well-known for their therapeutic potential. In this study, we focus on discovering novel inhibitors of MEK2 from flavonoids using virtual screening, molecular docking analyses, pharmacokinetic prediction, and molecular dynamics (MD) simulations. A library of drug-like flavonoids containing 1289 chemical compounds prepared in-house was screened against the MEK2 allosteric site using molecular docking. The ten highest-scoring compounds based on docking binding affinity (highest score: -11.3 kcal/mol) were selected for further analysis. Lipinski's rule of five was used to test their drug-likeness, followed by ADMET predictions to study their pharmacokinetic properties. The stability of the best-docked flavonoid complex with MEK2 was examined for a 150 ns MD simulation. The proposed flavonoids are suggested as potential inhibitors of MEK2 and drug candidates for cancer therapy.

摘要

世界上第二大致死原因是癌症。丝裂原活化蛋白激酶(MAPK)和细胞外信号调节激酶 1 和 2(ERK1/2)(MEK1/2)在不同的抗癌治疗靶点中脱颖而出。许多 MEK1/2 抑制剂已被批准并广泛用作抗癌药物。被称为黄酮类的天然化合物类具有很好的治疗潜力。在这项研究中,我们专注于使用虚拟筛选、分子对接分析、药代动力学预测和分子动力学(MD)模拟从黄酮类化合物中发现新型 MEK2 抑制剂。使用分子对接对包含 1289 种化学化合物的内部制备的类药黄酮类化合物库进行了针对 MEK2 变构位点的筛选。基于对接结合亲和力(最高得分为-11.3 kcal/mol)对得分最高的十个化合物进行了进一步分析。随后使用 Lipinski 五规则对它们的类药性进行测试,并进行 ADMET 预测以研究它们的药代动力学特性。使用 MD 模拟对与 MEK2 最佳对接的黄酮类化合物复合物的稳定性进行了 150 ns 的检验。所提出的黄酮类化合物有望成为 MEK2 的潜在抑制剂和癌症治疗的候选药物。

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