Over expression of aldehyde dehydrogenase (ALDH1A1) is one of the vital hallmarks of the self-renewal and differentiational cancer stem cells (CSCs). Till now, no selective ALDH1A1 inhibitor is commercially available in the market. So there is an urgent need to explore some novel molecules which can selectively inhibit ALDH1A1 to combat cancer. Presently, our work deals with the development of QSAR models of some theophylline-based molecules by conventional 2D-QSAR, hologram QSAR (HQSAR), and Bayesian classification modeling. The descriptors identified from these QSAR models give avenues to modulate the structure of theophylline-based compounds to a desirable biological end point. Molecular docking study reveals the selectivity of these molecules towards ALDH1A1 (PDB: 4WP7) and important binding residues (GLY 125, 458; THR 129; TRP 178; TYR 297; PHE 171, 466; VAL 174,
460; MET 175; HIS 293 etc.) for the interaction with the receptors. The current study may help to design novel compounds as selective ALDH1A1 inhibitors.
Keywords: Aldehyde dehydrogenase, theophylline-based inhibitors, QSAR, HQSAR, Bayesian modeling, molecular docking.
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