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Issue 9, 2017
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Integrating docking scores and key interaction profiles to improve the accuracy of molecular docking: towards novel B-RafV600E inhibitors

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Abstract

A set of ninety-eight B-RafV600E inhibitors was used for the development of a molecular docking based QSAR model using linear and non-linear regression models. The integration of docking scores and key interaction profiles significantly improved the accuracy of the QSAR models, providing reasonable statistical parameters (Rtrain2 = 0.935, Rtest2 = 0.728 and QCV2 = 0.905). The established MD-SVR (molecular docking based SMV regression) model as well as model screening of a natural product database was carried out and two natural products (quercetin and myricetin) with good prediction activities were biologically evaluated. Both compounds exhibited promising B-RafV600E inhibitory activities (ICQuercetin50 = 7.59 μM and ICMyricetin50 = 1.56 μM), suggesting a high reliability and good applicability of the established MD-SVR model in the future development of B-RafV600E inhibitors with high efficacy.

Graphical abstract: Integrating docking scores and key interaction profiles to improve the accuracy of molecular docking: towards novel B-RafV600E inhibitors

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Publication details

The article was received on 04 May 2017, accepted on 14 Jul 2017 and first published on 24 Jul 2017


Article type: Research Article
DOI: 10.1039/C7MD00229G
Citation: Med. Chem. Commun., 2017,8, 1835-1844
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    Integrating docking scores and key interaction profiles to improve the accuracy of molecular docking: towards novel B-RafV600E inhibitors

    C. Hu, K. Li, T. Yao, Y. Hu, H. Ying and X. Dong, Med. Chem. Commun., 2017, 8, 1835
    DOI: 10.1039/C7MD00229G

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