Activin-like kinase 5 (ALK-5) receptor represents an attractive object to treat cancer. Analyses on the quantitative structure-activity relationship were performed to explore the relationship between the molecular structure of 1,5-naphthyridine, pyrazole and quinazoline derivatives and the inhibition of the activin-like kinase 5. From a data set containing 59 compounds, various electronic descriptors were calculated using density functional theory (DFT) method; stereochemical descriptors (as molecular volume and area), polar surface area (PSA), log P and dragon descriptors were also calculated. The ordered predictor selection (OPS) algorithm, weighted principal component analysis (PCA) and Fisher's weights (FW), combined with sequential forward selection, were employed to select the most relevant descriptors to be employed in all partial least square regressions. Using this procedure, we selected the most informative descriptors and significant correlation coefficients were achieved (r2 = 0.74, q2= 0.83). Additional validation tests were carried out, indicating that the obtained model is robust and reliable and, consequently, it can be used to predict the biological activity of new compounds.
Keywords:
ALK-5; molecular modeling; feature selection; QSAR
