Abstract

The human immunodeficiency virus is a lethal pathology considered as a worldwide problem. The search for new strategies for the treatment of this disease continues to be a great challenge in the scientific community. In this study, a series of 107 derivatives of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine, previously evaluated experimentally against HIV-I reverse transcriptase, was used to model antiretroviral activity. A model of linear regression, implemented in the QSARINS software, was developed with a genetic algorithm for variable selection. The fit of its parameters was good and exhaustive validation, according to the OECD regulatory principles, was performed. Also, the applicability domain was established. In addition, its robustness (r(2) = 0.84), stability (Q(LOO)(2) = 0.81;Q(LMO)(2) = 0.80) and good predictive power (r(EXT)(2) = 0.85) is proved. So, it was used to predict the antiretroviral activity of eight compounds obtained by rational drug design. Finally, it can be affirmed that the proposed tools allow the rapid and economic identification of potential antiretroviral drugs.