Integrating docking scores and key interaction profiles to improve the accuracy of molecular docking: towards novel B-RafV600E inhibitors12. Issue 9 (10th August 2017)

• Record Type: Journal Article
• Authors: Hu, Chun-Qi; Li, Kang; Yao, Ting-Ting; Hu, Yong-Zhou; Ying, Hua-Zhou; Dong, Xiao-Wu
• Is Part Of: MedChemComm. Volume 8:Issue 9(2017)
• Page Start: 1835
• Page End: 1844
• Publication Date: 2017-08-10
• Subjects: Pharmaceutical chemistry -- Periodicals; 615.19
• DOI: 10.1039/c7md00229g
• Languages: English
• ISSNs: 2040-2503

Abstract

Abstract : A set of ninety-eight B-Raf V600E inhibitors was used for the development of a molecular docking based QSAR model using linear and non-linear regression models. Abstract : A set of ninety-eight B-Raf V600E 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 ( R train 2 = 0.935, R test 2 = 0.728 and Q CV 2 = 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-Raf V600E 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-Raf V600E inhibitors with high efficacy.