Acta Phys. -Chim. Sin. ›› 2015, Vol. 31 ›› Issue (11): 2191-2206.doi: 10.3866/PKU.WHXB201510134

• BIOPHYSICAL CHEMISTRY • Previous Articles     Next Articles

Accurate Activity Predictions of B-Raf Type II Inhibitors via Molecular Docking and QSAR Methods

Hai-Chun. LIU1,Shuai. LU1,Ting. RAN1,Yan-Min. ZHANG1,Jin-Xing. XU1,Xiao. XIONG1,An-Yang. XU1,Tao. LU1,2,*(),Ya-Dong. CHEN1,*()   

  1. 1 School of Basic Science, China Pharmaceutical University, Nanjing 211198, P. R. China
    2 State Key Laboratory of Natural Medcines, China Pharmaceutical University, Nanjing 210009, P. R. China
  • Received:2015-07-09 Published:2015-11-13
  • Contact: Tao. LU,Ya-Dong. CHEN;
  • Supported by:
    the National Natural Science Foundation of China(21102181);the National Natural Science Foundation of China(81302634)


B-Raf kinase plays an important role in the mitogen-activated protein kinase (MAPK) signaling transmission pathway and has been identified as an attractive target for cancer therapy. The exploitation of novel and efficient B-Raf inhibitors has become a hot research topic. In this study, we investigated quantitative structure-activity relationship (QSAR) to probe the origins of the inhibitory activities of B-Raf Type II inhibitors. We used structurally diverse B-Raf Type II inhibitors and an integrated docking and QSAR extended method. We focused mainly on two themes: bioactive conformations and descriptors. First, various molecular docking methods (Glide, Gold, LigandFit, Cdocker, and Libdock) were evaluated, and then all molecules were docked into the B-Raf active site to obtain the bioactive conformations. Secondly, based on the docking results, 16 scoring functions and 21 docking-generated energy-based descriptors were calculated to construct regression models. The results gave highly accurate fitting and had strong predictive abilities (M1: r2 = 0.852, r(CV)2 = 0.790, rpre2 = 0.864; M2: r2 = 0.738, r(CV)2 = 0.812, rpre2 = 0.8605). The important descriptors were also explored to elucidate the main factors influencing the inhibition activities. The models suggested that the scoring functions (G_Score, -ECD, Dock_Score, and PMF) and docking-generated energy-based descriptors (S(hb_ext), DE(int), and Emodel) were significant. Some new compounds that are potential B-Raf inhibitors were obtained through virtual screening and theoretical predictions using the established models. Such information is useful in guiding the design of novel and robust B-Raf Type II inhibitors.

Key words: B-Raf Type II inhibitor, Molecular docking, Scoring function, Docking-generated energybased descriptor, Quantitative structure-activity relationship model


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