Multivariate QSAR study of Modafinil derivatives with molecular descriptors derivated from SMILES notations and free softwares.

Despite many years of research, there are no approved medications for the treatment of reliance on stimulants such as cocaine, and treatment is focused on psychotherapy and abstinence, but about 50% of the individuals end up having relapses, mainly due to the symptoms of abstinence. The dopamine transport receptors (OAT) is a biological target for development of agents for treatment of psychostimulant dependence. This study aimed to obtain a QSAR model based on a set of 49 sulfanyl ethyl piperazines (all Modafinil derivatives) assayed as OAT inhibitors. We used only 20 molecular descriptors with the SMILES notation obtained in free platform ChemDes (http://www.scbdd.com/chemdes). The Variable selection (with Ordered Predictors Selection approach) and the model building were carried out in the QSAR Modeling (http://lqta.iqm.unicamp.br). The validation was performed in the same software and in the Xternal Validation 1.2 (https://sites.google.com/site/dtclabxvplus). A PLS model with good internal and external statistical features was obtained with four molecular descriptors: two BCUT weighted by polarizability and volume, one minimum E-state value, and one MOE-type descriptor based on partial charges and surface area. The presence of electronic characteristics agrees with reported information that the mode of binding of both Modafinil and cocaine to the OAT receptor is dependent on hydrogen bonds. Results show that the obtained model, although simple, have potential and may be suitable to propose new derivatives and for use in virtual screening studies.