BioLab

Drug Discovery

The challenge in a phenotypic drug discovery strategy is to fully understand and elucidate, in addition to the resolution of the mechanism of action (MoA), identifying with high resolution the molecular target(s) affected by the drug and responsible for its pharmacological activity. Recently, a model has been proposed that combines three data sources: the chemical structure, the biological routes and the phenotypic responses. Although it is an advance, the model has the limitation of the low statistical significance of the results. 

Based on the scientific literature and our previous experience, our model also proposes the combination of three data sources, ordered from higher to lower “relevance”. 1) The phenotypic responses; 2) The biological targets involved in the biological routes; and 3) The chemical structure. Our proposal uses as a basic phenotypic tool the possible cell cycle changes induced by the compounds under study. It should be noted that none of the methods of predicting MoA use cell cycle data. However, in our trajectory we have found that cell cycle data play a relevant role in the study of antitumor compounds. Thus, the results have allowed us to define general aspects of antiproliferative or cytotoxic MoA of the compounds under investigation. To the experimental data of cell cycle it will be added the specific tests of changes of protein expression and of enzymatic activity inhibition. These data are complemented by computational studies that relate the chemical structure of small molecules and the interaction with molecular targets.