Uso da Bioinformática para selecionar moléculas candidatas a fármacos

Abstract

The development of new drugs can present several problems, an important bottleneck in this process being the ability to reconcile a molecule that is a potent pharmacological inhibitor and that also has its synthesis possible to be carried out. Previous computational studies must be carried out to target molecules with good pharmacokinetic parameters, high biological activity and also a great possibility of being synthesized. Among several computational tools used in the study of new drugs, there are those used to predict pharmacokinetic parameters. Such tools are computational platforms of easy access and execution. After identifying and validating a pharmacological target, for example kinase enzymes in cancer, promising molecules can be designed for this target. If the type of cancer is brain, studies of promising molecules with the ability to cross the blood-brain barrier can contribute significantly. Thus, the objective of this study is to carry out computational studies for the selection of promising molecules for the treatment of brain cancer. To carry out this study, 98 molecules were selected. As a criterion for this selection was, firstly, to evaluate the possibility of synthesizing these molecules. Then computational studies were carried out to evaluate pharmacokinetic parameters, ability to inhibit kinases and to cross the blood-brain barrier. The result obtained in this study allowed the selection of five most promising molecules. Such molecules can be synthesized and tested in in vitro experiments. It can be concluded, therefore, that this study allowed the reduction of a considered high number of proposed molecules to a reduced number of those considered more promising, thus reducing the time and money for the development of promising molecules for the treatment of this type of cancer.