Literature DB >> 16854057

Modeling the ligand-receptor interaction for a series of inhibitors of the capsid protein of enterovirus 71 using several three-dimensional quantitative structure-activity relationship techniques.

Yi-Yu Ke1, Thy-Hou Lin.   

Abstract

The structure of enterovirus 71 (EV71) capsid protein VP1 has been constructed by using homology modeling and molecular dynamics simulation techniques. The ligand structures were a series of EV71 VP1 inhibitors synthesized by Shia et al. in 2002 and Chern et al. in 2004. The training set was selected by the VOLSURF4.1/PCA program and the IC50 values varied from 0.06 to 10.83 microm. Then, the training set was analyzed by the following three-dimensional quantitative structure-activity relationship techniques: CoMFA, CoMSIA, CATALYST4.9, and VOLSURF4.1/PCA. The model generated by a two-stage flexible docking procedure and without any structural alignment has far more significant statistics. Highly accurate activities for the test sets were then predicted by the top hypothesis of the CATALYST program and were compared with those predicted by CoMFA, CoMSIA, and VOLSURF. These studies identified some important clues for searching or making more potent inhibitors against the EV71 infection.

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Year:  2006        PMID: 16854057     DOI: 10.1021/jm0511886

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  5 in total

Review 1.  Back to the future: Advances in development of broad-spectrum capsid-binding inhibitors of enteroviruses.

Authors:  Anna Egorova; Sean Ekins; Michaela Schmidtke; Vadim Makarov
Journal:  Eur J Med Chem       Date:  2019-06-11       Impact factor: 6.514

2.  More-powerful virus inhibitors from structure-based analysis of HEV71 capsid-binding molecules.

Authors:  Luigi De Colibus; Xiangxi Wang; John A B Spyrou; James Kelly; Jingshan Ren; Jonathan Grimes; Gerhard Puerstinger; Nicola Stonehouse; Thomas S Walter; Zhongyu Hu; Junzhi Wang; Xuemei Li; Wei Peng; David Rowlands; Elizabeth E Fry; Zihe Rao; David I Stuart
Journal:  Nat Struct Mol Biol       Date:  2014-02-09       Impact factor: 15.369

3.  Study of the biological activity of novel synthetic compounds with antiviral properties against human rhinoviruses.

Authors:  Samuela Laconi; Maria A Madeddu; Raffaello Pompei
Journal:  Molecules       Date:  2011-04-26       Impact factor: 4.411

4.  Comparative study between deep learning and QSAR classifications for TNBC inhibitors and novel GPCR agonist discovery.

Authors:  Lun K Tsou; Shiu-Hwa Yeh; Shau-Hua Ueng; Chun-Ping Chang; Jen-Shin Song; Mine-Hsine Wu; Hsiao-Fu Chang; Sheng-Ren Chen; Chuan Shih; Chiung-Tong Chen; Yi-Yu Ke
Journal:  Sci Rep       Date:  2020-10-08       Impact factor: 4.379

5.  Potent antiviral agents fail to elicit genetically-stable resistance mutations in either enterovirus 71 or Coxsackievirus A16.

Authors:  James T Kelly; Luigi De Colibus; Lauren Elliott; Elizabeth E Fry; David I Stuart; David J Rowlands; Nicola J Stonehouse
Journal:  Antiviral Res       Date:  2015-10-30       Impact factor: 5.970

  5 in total

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