Abstract

Cytochrome P450 isozyme 1A2 (CYP1A2) is one main xenobiotic metabolizing enzyme in humans. It has been associated with the bioactivation of procarcinogens, including 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), a tobacco specific and potent pulmonary carcinogen. This work describes the computational design and in-silico screening of potential CYP1A2 inhibitors, their chemical synthesis, and enzymatic characterization with the ultimate aim of assessing their potential as cancer chemopreventive agents. To achieve this, a combined classifiers model was used to screen a library of quinazoline-based molecules against known CYP1A2 inhibitors, non-inhibitors, and substrates to predict which quinazoline candidates had a better probability as an inhibitor. Compounds with high probability of CYP1A2 inhibition were further computationally evaluated via Glide docking. Candidates predicted to have selectivity and high binding affinity for CYP1A2 were synthesized and assayed for their enzymatic inhibition of CYP1A2, leading to the discovery of novel and potent quinazoline-based CYP1A2 inhibitors.

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