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. 2015 May 29;16(6):12307-23.
doi: 10.3390/ijms160612307.

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors

Huiding Xie  1   2 , Lijun Chen  3 , Jianqiang Zhang  4 , Xiaoguang Xie  5 , Kaixiong Qiu  6 , Jijun Fu  7
Affiliations

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors

Huiding Xie et al. Int J Mol Sci. .

Abstract

B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes. In succession, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on 39 imidazopyridine BRIs to build three dimensional quantitative structure-activity relationship (3D QSAR) models based on both pharmacophore and docking alignments. The CoMSIA model based on the pharmacophore alignment shows the best result (q(2) = 0.621, r(2)(pred) = 0.885). This 3D QSAR approach provides significant insights that are useful for designing potent BRIs. In addition, the obtained best pharmacophore model was used for virtual screening against the NCI2000 database. The hit compounds were further filtered with molecular docking, and their biological activities were predicted using the CoMSIA model, and three potential BRIs with new skeletons were obtained.

Keywords: 3D QSAR; B-Raf inhibitors; imidazopyridine; pharmacophore; virtual screening.

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Figures

Figure 1
Figure 1
The selected GALAHAD model includes two acceptor atoms (green), three donor atoms (magenta) and three hydrophobes (cyan). The sphere sizes indicate query tolerances.
Figure 2
Figure 2
(a) Pharmacophore-based alignment of the total data set; and (b) Docking-based alignment of the total data set.
Figure 3
Figure 3
Plots of observed vs. predicted activities of the training set and test set molecules from CoMSIA analysis.
Figure 4
Figure 4
(a) Steric contour maps in combination with compounds 18 and 10: green contours refer to sterically favored regions; yellow contours indicate sterically disfavored areas; (b) Electrostatic contour maps in combination with compound 18: blue contours refer to regions where positively charged substituents are favored; red contours indicate regions where negatively charged substituents are favored; (c) Hydrophobic contour maps in combination with compounds 18 and 10: yellow contours indicate regions where hydrophobic substituents are favored; white contours refer to regions where hydrophilic substituents are favored; (d) HBD contour map in combination with compound 18: cyan contours indicate HBD substituents in this region are favorable to activity; purple contours represent that HBD groups in this area are unfavorable; and (e) HBA contour maps in combination with compound 18: magenta contours show regions where HBA substituents are expected; red contours refer to areas where HBA substituents are unexpected.
Figure 4
Figure 4
(a) Steric contour maps in combination with compounds 18 and 10: green contours refer to sterically favored regions; yellow contours indicate sterically disfavored areas; (b) Electrostatic contour maps in combination with compound 18: blue contours refer to regions where positively charged substituents are favored; red contours indicate regions where negatively charged substituents are favored; (c) Hydrophobic contour maps in combination with compounds 18 and 10: yellow contours indicate regions where hydrophobic substituents are favored; white contours refer to regions where hydrophilic substituents are favored; (d) HBD contour map in combination with compound 18: cyan contours indicate HBD substituents in this region are favorable to activity; purple contours represent that HBD groups in this area are unfavorable; and (e) HBA contour maps in combination with compound 18: magenta contours show regions where HBA substituents are expected; red contours refer to areas where HBA substituents are unexpected.
Figure 5
Figure 5
Plots of QFIT values vs. biological activity (pIC50 values) of 39 inhibitors.
Figure 6
Figure 6
Plots of C_score values vs. biological activity (pIC50 values) of 39 inhibitors.
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