Identification of the Structural Features of Guanine Derivatives as MGMT Inhibitors Using 3D-QSAR Modeling Combined with Molecular Docking

被引:22
|
作者
Sun, Guohui [1 ]
Fan, Tengjiao [1 ]
Zhang, Na [1 ]
Ren, Ting [1 ]
Zhao, Lijiao [1 ]
Zhong, Rugang [1 ]
机构
[1] Beijing Univ Technol, Coll Life Sci & Bioengn, Beijing Key Lab Environm & Viral Oncol, Beijing 100124, Peoples R China
来源
MOLECULES | 2016年 / 21卷 / 07期
基金
中国国家自然科学基金;
关键词
MGMT; inhibitors; 3D-QSAR; CoMFA; CoMSIA; docking; DNA-REPAIR PROTEIN; INTERSTRAND CROSS-LINKS; INDEX ANALYSIS COMSIA; O-6-ALKYLGUANINE-DNA ALKYLTRANSFERASE; O-6-METHYLGUANINE-DNA METHYLTRANSFERASE; SIMILARITY INDEXES; FIELD ANALYSIS; TUMOR-CELLS; PHASE-II; O-6-BENZYLGUANINE;
D O I
10.3390/molecules21070823
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
DNA repair enzyme O-6-methylguanine-DNA methyltransferase (MGMT), which plays an important role in inducing drug resistance against alkylating agents that modify the O-6 position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have been synthesized over the past decades to improve the chemotherapeutic effects of O-6-alkylating agents. In the present study, we performed a three-dimensional quantitative structure activity relationship (3D-QSAR) study on 97 guanine derivatives as MGMT inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Three different alignment methods (ligand-based, DFT optimization-based and docking-based alignment) were employed to develop reliable 3D-QSAR models. Statistical parameters derived from the models using the above three alignment methods showed that the ligand-based CoMFA (Q(cv)(2) = 0.672 and R-ncv(2) = 0.997) and CoMSIA (Q(cv)(2) = 0.703 and R-ncv(2) = 0.946) models were better than the other two alignment methods-based CoMFA and CoMSIA models. The two ligand-based models were further confirmed by an external test-set validation and a Y-randomization examination. The ligand-based CoMFA model (Q(ext)(2) = 0.691, R-pred(2) = 0.738 and slope k = 0.91) was observed with acceptable external test-set validation values rather than the CoMSIA model (Q(ext)(2) = 0.307, R-pred(2) = 0.4 and slope k = 0.719). Docking studies were carried out to predict the binding modes of the inhibitors with MGMT. The results indicated that the obtained binding interactions were consistent with the 3D contour maps. Overall, the combined results of the 3D-QSAR and the docking obtained in this study provide an insight into the understanding of the interactions between guanine derivatives and MGMT protein, which will assist in designing novel MGMT inhibitors with desired activity.
引用
收藏
页数:21
相关论文
共 50 条
  • [31] Molecular modeling studies of atorvastatin analogues as HMGR inhibitors using 3D-QSAR, molecular docking and molecular dynamics simulations
    Wang, Zhi
    Cheng, Liping
    Kai, Zhenpeng
    Wu, Fanhong
    Liu, Zhuoyu
    Cai, Minfeng
    BIOORGANIC & MEDICINAL CHEMISTRY LETTERS, 2014, 24 (16) : 3869 - 3876
  • [32] 3D-QSAR and Molecular Docking Studies of p-Aminobenzoic Acid Derivatives to Explore the Features Requirements of Alzheimer Inhibitors
    El Khatabi, Khalil
    Aanouz, Ilham
    El-mernissi, Reda
    Khaldan, Ayoub
    Ajana, Mohammed Aziz
    Bouachrine, Mohammed
    Lakhlifi, Tahar
    ORBITAL-THE ELECTRONIC JOURNAL OF CHEMISTRY, 2020, 12 (04): : 172 - 181
  • [33] Molecular modeling studies on series of Btk inhibitors using docking, structure-based 3D-QSAR and molecular dynamics simulation: a combined approach
    Pavithra K. Balasubramanian
    Anand Balupuri
    Seung Joo Cho
    Archives of Pharmacal Research, 2016, 39 : 328 - 339
  • [34] Molecular modeling studies on series of Btk inhibitors using docking, structure-based 3D-QSAR and molecular dynamics simulation: a combined approach
    Balasubramanian, Pavithra K.
    Balupuri, Anand
    Cho, Seung Joo
    ARCHIVES OF PHARMACAL RESEARCH, 2016, 39 (03) : 328 - 339
  • [35] Docking and 3D-QSAR investigations of pyrrolidine derivatives as potent neuraminidase inhibitors
    Sun, Jiaying
    Mei, Hu
    CHEMICAL BIOLOGY & DRUG DESIGN, 2012, 79 (05) : 863 - 868
  • [36] 3D-QSAR and docking studies of piperidine carboxamide derivatives as ALK inhibitors
    Wang, Peng
    Cai, Jin
    Chen, Junqing
    Li, Lushen
    Sun, Chunlong
    Xue, Bai
    Ji, Min
    MEDICINAL CHEMISTRY RESEARCH, 2014, 23 (05) : 2576 - 2583
  • [37] 3D-QSAR and docking studies of piperidine carboxamide derivatives as ALK inhibitors
    Peng Wang
    Jin Cai
    Junqing Chen
    Lushen Li
    Chunlong Sun
    Bai Xue
    Min Ji
    Medicinal Chemistry Research, 2014, 23 : 2576 - 2583
  • [38] 3D-QSAR, molecular docking, and molecular dynamics analysis of dihydrodiazaindolone derivatives as PARP-1 inhibitors
    Jing Zhao
    Na Yu
    Xuemin Zhao
    Wenxuan Quan
    Mao Shu
    Journal of Molecular Modeling, 2023, 29
  • [39] 3D-QSAR, molecular docking and molecular dynamics simulations of oxazepane amidoacetonitrile derivatives as novel DPPI inhibitors
    Huang, Lei-Lei
    Han, Jie
    Ran, Jian-Xiong
    Chen, Xiu-Ping
    Wang, Zhong-Hua
    Wu, Fan-Hong
    JOURNAL OF MOLECULAR STRUCTURE, 2018, 1168 : 223 - 233
  • [40] 3D-QSAR, molecular docking, and molecular dynamics analysis of dihydrodiazaindolone derivatives as PARP-1 inhibitors
    Zhao, Jing
    Yu, Na
    Zhao, Xuemin
    Quan, Wenxuan
    Shu, Mao
    JOURNAL OF MOLECULAR MODELING, 2023, 29 (05)