About 132 thousand cases of melanoma (more severe type of skin cancer) were registered in 2014
according to the World Health Organization. This type of cancer significantly affects the quality of life of individuals.
Caffeine has shown potential inhibitory effect against epithelial cancer. In this study, it was proposed to
obtain new caffeine-based molecules with potential epithelial anticancer activity. For this, a training set of 21
molecules was used for pharmacophore perception procedures. Multiple linear regression analyses were used to
propose mono-, bi-, tri-, and tetra-parametric models applied in the prediction of the activity. The generated
pharmacophore was used to select 350 molecules available at the ZINCpharmer server, followed by reduction to
24 molecules, after selection using the Tanimoto index, yielding 10 molecules after final selection by predicted
activity values > 1.5229. These ten molecules had better pharmacokinetic properties than the other ones used as
reference and within the clinically significant limits. Only two molecules show minor hits of toxicity and were
submitted to molecular docking procedures, showing BFE (binding free energy) values lower than the reference
values. Statistical analyses indicated strong negative correlations between BFE and pharmacophoric properties
(high influence on BFE lowering) and practically null correlation between BFE and BBB. The two most promising
molecules can be indicated as candidates for further in vitro and in vivo analyzes.
Keywords: Epithelial cancer, caffeine, Chk1, Molecular modeling, multiple linear regression, Pharmacokinetic and toxicological properties.
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