Computer-aided discovery of new FGFR-1 inhibitors followed by in vitro validation

被引:17
|
作者
Alabed, Shada J. [1 ]
Khanfar, Mohammad [1 ]
Taha, Mutasem O. [2 ]
机构
[1] Univ Jordan, Fac Pharm, Dept Pharmaceut Sci, Amman, Jordan
[2] Univ Jordan, Fac Pharm, Dept Pharmaceut Sci, Drug Discovery Unit, Amman, Jordan
关键词
dbCICA; FGFR-1; pharmacophore; QSAR; virtual search; INTERMOLECULAR CONTACTS ANALYSIS; QUANTITATIVE STRUCTURE-PROPERTY; PROTEIN-LIGAND INTERACTIONS; SILICO SCREENING REVEAL; QSAR ANALYSIS; DRUG DESIGN; BIOLOGICAL EVALUATION; PHARMACOPHORE; DOCKING; RECEPTORS;
D O I
10.4155/fmc-2016-0056
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Aim: FGFR-1 is an oncogenic kinase involved in several cancers. FGFR1-specific inhibitors have shown promising results against several human cancers prompting us to model this interesting target. Toward the end, we implemented elaborate ligand-based and structure-based computational workflows to explore the pharmacophoric requirements for potent FGFR-1 inhibitors. Results & methodology: Structure-based and ligand-based modeling applied on 59 diverse FGFR-1 inhibitors yielded novel pharmacophore and quantitative structure-activity relationship models that were used to scan the National Cancer Institute's structural database for novel leads. Four potent hits were captured, with the most active having IC50 of 426 nM. Identities and purities of active hits were established using nuclear magnetic resonance and mass spectroscopy. Conclusion: Elaborate ligand-based (pharmacophore/QSAR) and structure-based (docking-based comparative intermolecular contacts analysis) modeling provided deep understanding of ligand binding within FGFR-1 as evidenced by the virtually captured new potent leads.
引用
收藏
页码:1841 / 1869
页数:29
相关论文
共 50 条
  • [21] Computational chemistry and computer-aided drug discovery: part 1
    Bajorath, Juergen
    FUTURE MEDICINAL CHEMISTRY, 2016, 8 (14)
  • [22] COMPUTER-AIDED VALIDATION OF FORMAL SPECIFICATIONS
    MUKHERJEE, P
    SOFTWARE ENGINEERING JOURNAL, 1995, 10 (04): : 133 - 140
  • [23] Computer-aided design of thrombin inhibitors
    Caflisch, A
    Wälchli, R
    Ehrhardt, C
    NEWS IN PHYSIOLOGICAL SCIENCES, 1998, 13 : 182 - 189
  • [24] Computer-aided discovery of phenylpyrazole based amides as potent S6K1 inhibitors
    Yin, Yan
    Sun, Yuxing
    Zhao, Lianhua
    Pan, Jinpeng
    Feng, Yangbo
    RSC MEDICINAL CHEMISTRY, 2020, 11 (05): : 583 - 590
  • [25] Special issue on computer-aided drug discovery
    McCammon, J. Andrew
    BIOPOLYMERS, 2016, 105 (01) : 1 - 1
  • [26] Artificial Intelligence for Computer-Aided Drug Discovery
    Kate, Aditya
    Seth, Ekkita
    Singh, Ananya
    Chakole, Chandrashekhar Mahadeo
    Chauhan, Meenakshi Kanwar
    Singh, Ravi Kant
    Maddalwar, Shrirang
    Mishra, Mohit
    DRUG RESEARCH, 2023, 73 (07) : 369 - 377
  • [27] Systems Biology and Computer-Aided Drug Discovery
    Lilburn, Timothy G.
    Wang, Yufeng
    CURRENT COMPUTER-AIDED DRUG DESIGN, 2006, 2 (03) : 267 - 274
  • [28] Computer-Aided Drug Discovery in Plant Pathology
    Shanmugam, Gnanendra
    Jeon, Junhyun
    PLANT PATHOLOGY JOURNAL, 2017, 33 (06): : 529 - 542
  • [29] COMPUTER-AIDED DISCOVERY AND CATEGORISATION OF PERSONALITY AXIOMS
    Kramer, Simon
    JOURNAL OF APPLIED LOGICS-IFCOLOG JOURNAL OF LOGICS AND THEIR APPLICATIONS, 2014, 1 (02): : 107 - 133
  • [30] Application of Computer-Aided Drug Repurposing in the Search of New Cruzipain Inhibitors: Discovery of Amiodarone and Bromocriptine Inhibitory Effects
    Bellera, Carolina L.
    Balcazar, Dario E.
    Alberca, Lucas
    Labriola, Carlos A.
    Talevi, Alan
    Carrillo, Carolina
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2013, 53 (09) : 2402 - 2408