化学学报 ›› 2013, Vol. 71 ›› Issue (10): 1396-1403.DOI: 10.6023/A13040375 上一篇    下一篇

研究论文

螺环吲哚类MDM2抑制剂的分子对接、定量构效关系和分子动力学模拟

李博a, 周锐a, 何谷a,b, 郭丽a, 黄维c   

  1. a 四川大学华西药学院 成都 610041;
    b 四川大学华西医院 生物治疗国家重点实验室 成都 610041;
    c 成都中医药大学药学院 成都 611137
  • 收稿日期:2013-04-06 出版日期:2013-10-14 发布日期:2013-08-25
  • 通讯作者: 何谷,E-mail:heguscu@163.com;郭丽,E-mail:rosaguoli2000@yahoo.com.cn E-mail:heguscu@163.com;rosaguoli2000@yahoo.com.cn
  • 基金资助:

    项目受国家自然科学基金(Nos. 81001357, 81273471)和中药资源系统研究与开发利用省部共建国家重点实验室培育基地开放课题资助.

Molecular Docking, QSAR and Molecular Dynamics Simulation on Spiro-oxindoles as MDM2 Inhibitors

Li Boa, Zhou Ruia, He Gua,b, Guo Lia, Huang Weic   

  1. a West China School of Pharmacy, Sichuan University, Chengdu 610041;
    b State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, 610041;
    c School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu 611137
  • Received:2013-04-06 Online:2013-10-14 Published:2013-08-25
  • Supported by:

    Project supported by the National Natural Science Foundation of China (Nos. 81001357, 81273471) and the Open Research Fund of State Key Laboratory Breeding Base of Systematic Research, Development and Utilization of Chinese Medicine.

采用分子对接、三维定量构效关系(3D-QSAR)和分子动力学方法研究了21个螺环吲哚类化合物与MDM2蛋白的相互作用, 并建立了相关预测模型. 比较分子场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA)模型的交互验证相关系数q2分别为0.573 和0.651, 非交互验证相关系数r2分别为0.948和0.980. 分子对接得到的结合模式与分子动力学模拟得到的结果一致, 结合模式表明该类螺环吲哚化合物主要通过疏水相互作用和氢键与MDM2结合. 基于上述相互作用模型设计并合成了6个新结构螺环吲哚化合物, 并在MDM2高表达的前列腺癌LNCaP细胞株上测定其活性, 结果表明化合物5, 6的半数抑制浓度均低于1μg·mL-1, 可作为新的抗肿瘤药物先导化合物进一步深入研究. 本研究对以MDM2为靶点的新结构螺环吲哚类抑制剂的开发提供了理论和实验依据.

关键词: 螺环吲哚衍生物, 分子对接, 分子动力学, 比较分子场分析, 比较分子相似性指数分析

Inhibition of the MDM2-p53 interaction is considered to be a new therapeutic strategy to activate wild-type p53 in tumors. Recently, a series of potent and specific small-molecule spiro-oxindole inhibitors of the MDM2 were reported. In the current study, the interaction modes between 21 spiro-oxindole MDM2 inhibitors and the protein were studied by using the combination of molecular docking, molecular dynamics simulation and three-dimensional quantitative structure-activity relationships (3D-QSAR). The QSAR predictive models were established by using comparative molecular field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) techniques. The predictive power of the 3D-QSAR models were determined from external test sets that were excluded during model development. The inhibitors in test sets were given exactly the same pretreatment as the inhibitors in the corresponding training sets. The correlation between the experimental and predicted activity for all models was calculated as a predictive r2 value. With the CoMFA model, the cross-validated value (q2) was 0.573, the non-cross-validated value (r2) was 0.948. And with the CoMSIA model, the corresponding q2 and r2 were 0.651 and 0.98, respectively. The interaction mode obtained by molecular docking was in agreement with the results of molecular dynamics simulations, the interaction mode revealed that the hydrophobic interaction and H-bond played an important role in the binding of spiro-oxindole derivatives and MDM2. Compounds designed by our group were synthesized and tested their in vitro cytotoxic activities against the MDM2 positive prostatic carcinoma LNCaP cell line. Two compounds, namely 5 and 6, with favorable scores from the CoMFA and CoMSIA models, showed potent cytotoxic activities with IC50 values lower than 1.0 μg·mL-1. The result was corresponding with that in experiment. And it was very significance to discover novel spiro-oxindole inhibitors which are mainly aimed at the MDM2-p53 interaction. It was expected that the information provided here was helpful for the study toward more accurate structure based on 3D-QSAR modeling and anti-tumor drug design and discovery.

Key words: Spiro spiro-oxindole derivatives, Molecular molecular docking, Molecular molecular dynamics, Comparative comparative molecular field analysis, Comparative comparative molecular similarity indices analysis