Dihydrofolate reductase inhibitors: A quantitative structure-activity relationship study using 2D and 3D-QSAR methods

JUAN C. GARRO MARTINEZ; MATIAS F. ANDRADA; ESTEBAN G. VEGA-HISSI; FRANCISCO M. GARIBOTTO; MANUEL NOGUERAS; RICAURTE RODRÍGUEZ; JUSTO COBO; RICARDO D. ENRIZ; MARIO R. ESTRADA

MEDICINAL CHEMISTRY RESEARCH

BIRKHAUSER BOSTON INC

Año: 2017

1054-2523

In this work, we study the structure-activity relationship of a series of Dihydrofolate reductase (DHFR) inhibitors by 2D and 3D-QSAR techniques. The 2D-QSAR models were developed by using two different types of topological molecular descriptors, PaDEL and Dragon descriptors. The models showed an excellent predictive power, R2train=0.916 and R2val=0.806 for the PaDEL, and R2train=0.952 and R2val=0.963 for those obtained with Dragon descriptors. Simple molecular descriptors as maxHCsats, IC3, SPI, SIC2, and GATS5p were adequate to obtain predictive models. The 3D-QSAR was performed through three variable selected approaches, PLS, FDD and UVE-PLS using the Open3DQSAR software. All the 2D and 3D models were validated using two compounds (number 24 and 25) which were synthesized and presented here for the first time. Their biological activities were correctly predicted by all the QSAR models. Finally, we proposed three compounds (26, 27 and 28) which showed a high predicted DHFR inhibitory activity. Molecular docking study suggested that compounds bind to receptor similarly to the most active inhibitors.