Estudos QSAR de derivados de pirimidonas, pirimidinas e piridopirazinas carboxamidas inibidoras da HIV 1 integrase

Abstract

The computer-aided drug design field have attracted attention with regard to the discovery of new antiretroviral for use in AIDS pharmacotherapy. Thus, the aim of this study was to develop mathematical models that can predict the anti HIV1-IN activity of analogues not synthesized from pyrimidones, pyrimidines and pyridopyrazine carboxamides, reducing the time to obtain new prototypes of drugs. Therefore, it was selected from the literature, a set of 199 compounds described as strand transfer reaction inhibitors and developed 2D and 3D QSAR studies. For the 2D QSAR was used the Ordered Predictors Selection (OPS) methodology in order to develop the variable selection and Fractional Factorial Design (FFD) and OPS for the 3D QSAR. The models in both studies were constructed using partial least squares (PLS). Regarding the 3D QSAR studies, were employed two different methodologies for the calculation of the molecular interaction fields (MIFs): GRID and GRIND (GRid-INdependent descriptors). In addition, they were also used descriptors of pharmacokinetic properties from the Volsurf+ software (extracted from MIFs generated with GRID) for building models in combination with 2D descriptors. The statistical models with good quality were used to predict the activities of a second data set (prediction set, N=145). The resultants predictions were satisfactory. The Williams and Euclidean applicability domains for the set of samples reveal that the predictions did not occur by extrapolation. Moreover, the descriptor ET (total energy of the molecule), selected by the QSAR 2D model is consistent with earlier findings. Further, for the 3D study, the most relevant characteristics (N1-N1 interactions and DRY-O) are coherent with the pharmacophore of the class under study.