Pharmacophore modeling and virtual screening studies to identify new c-Met inhibitors.

Abstract

Mesenchymal epithelial transition factor (c-Met) is an attractive target for cancer therapy. Three-dimensional pharmacophore hypotheses were built based on a set of known structurally diverse c-Met inhibitors. The best pharmacophore model, which identified inhibitors with an associated correlation coefficient of 0.983 between their experimental and estimated IC(50) values, consisted of two hydrogen-bond acceptors, one hydrophobic, and one ring aromatic feature. The highly predictive power of the model was rigorously validated by test set prediction and Fischer's randomization method. The high values of enrichment factor and receiver operating characteristic (ROC) score indicated the model performed fairly well at distinguishing active from inactive compounds. The model was then applied to screen compound database for potential c-Met inhibitors. A filtering protocol, including druggability and molecular docking, were also applied in hits selection. The final 38 molecules, which exhibited good estimated activities, desired binding mode and favorable drug likeness were identified as potential c-Met inhibitors. Their novel backbone structures could be served as scaffolds for further study, which may facilitate the discovery and rational design of potent c-Met kinase inhibitors.

• Authors: Wenting Tai, Tao Lu, Haoliang Yuan, Fengxiao Wang, Haichun Liu, Shuai Lu, Ying Leng, Weiwei Zhang, Yulei Jiang, Yadong Chen
• Journal: Journal of molecular modeling (J Mol Model) Vol. 18 Issue 7 Pg. 3087-100 (Jul 2012) ISSN: 0948-5023 [Electronic] Germany
• PMID: 22203475 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)

Chemical References

• Protein Kinase Inhibitors
• Proto-Oncogene Proteins c-met

Topics

• Computer Simulation
• Databases, Factual
• Hydrogen Bonding
• Hydrophobic and Hydrophilic Interactions
• Models, Molecular
• Protein Binding
• Protein Kinase Inhibitors (chemistry, pharmacology)
• Proto-Oncogene Proteins c-met (antagonists & inhibitors, chemistry)
• Quantitative Structure-Activity Relationship
• ROC Curve
• Reproducibility of Results