Journal
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Volume 16, Issue 6, Pages 13407-13426Publisher
MDPI AG
DOI: 10.3390/ijms160613407
Keywords
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Funding
- Hi-Tech Research and Development Program of China [2014AA01A302, 2012AA020308, 2012AA01A305]
- National Natural Science Foundation of China [81430084]
- Ministry of Science and Technology of China [2015CB910304]
- National Science and Technology Major Project Key New Drug Creation and Manufacturing Program [2014ZX09507002]
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The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it is of high interest to find FGFR inhibitors with novel scaffolds. In this study, a combinatorial three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed based on previously reported FGFR1 inhibitors with diverse structural skeletons. This model was evaluated for its prediction performance on a diverse test set containing 232 FGFR inhibitors, and it yielded a SD value of 0.75 pIC(50) units from measured inhibition affinities and a Pearson's correlation coefficient R-2 of 0.53. This result suggests that the combinatorial 3D-QSAR model could be used to search for new FGFR1 hit structures and predict their potential activity. To further evaluate the performance of the model, a decoy set validation was used to measure the efficiency of the model by calculating EF (enrichment factor). Based on the combinatorial pharmacophore model, a virtual screening against SPECS database was performed. Nineteen novel active compounds were successfully identified, which provide new chemical starting points for further structural optimization of FGFR1 inhibitors.
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