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

Xie H, Chen L, Zhang J, Xie X, Qiu K, Fu J - Int J Mol Sci (2015)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry, Yunnan University, Kunming 650091, China. front701228.student@sina.com.

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.

No MeSH data available.


Related in: MedlinePlus

(a) Pharmacophore-based alignment of the total data set; and (b) Docking-based alignment of the total data set.
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ijms-16-12307-f002: (a) Pharmacophore-based alignment of the total data set; and (b) Docking-based alignment of the total data set.

Mentions: The structural alignment of compounds is a crucial step in the development of successful 3D QSAR models. In order to obtain reasonable results, all compounds of the data set were aligned according to both pharmacophore and molecular docking to derive CoMFA and CoMSIA models in current study. Figure 2a,b show pharmacophore-based and docking-based alignments of all the 39 molecules used in 3D QSAR models, respectively.


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

Xie H, Chen L, Zhang J, Xie X, Qiu K, Fu J - Int J Mol Sci (2015)

(a) Pharmacophore-based alignment of the total data set; and (b) Docking-based alignment of the total data set.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4490445&req=5

ijms-16-12307-f002: (a) Pharmacophore-based alignment of the total data set; and (b) Docking-based alignment of the total data set.
Mentions: The structural alignment of compounds is a crucial step in the development of successful 3D QSAR models. In order to obtain reasonable results, all compounds of the data set were aligned according to both pharmacophore and molecular docking to derive CoMFA and CoMSIA models in current study. Figure 2a,b show pharmacophore-based and docking-based alignments of all the 39 molecules used in 3D QSAR models, respectively.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry, Yunnan University, Kunming 650091, China. front701228.student@sina.com.

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.

No MeSH data available.


Related in: MedlinePlus