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 ² _LOO = 0.81; Q ² _LMO = 0.80) and good predictive power (r ² _EXT = 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.

人类免疫缺陷病毒是一种致命的病理，被认为是世界范围的问题。寻找新的治疗该疾病的策略仍然是科学界的巨大挑战。在这项研究中，使用1-107（1-（（2-羟乙氧基）甲基）-6-（苯硫基）胸腺嘧啶的一系列107衍生物（先前已针对HIV-1逆转录酶进行了实验评估）用于模拟抗逆转录病毒活性。使用遗传算法开发了在QSARINS软件中实现的线性回归模型，用于变量选择。其参数的拟合度很好，并且根据OECD监管原则进行了详尽的验证。此外，建立了适用性域。此外，它的鲁棒性（r ²  = 0.84），稳定性（Q ² _LOO  = 0.81； 证明Q ² _LMO  = 0.80）和良好的预测能力（r ² _EXT = 0.85）。因此，它被用来预测通过合理药物设计获得的八种化合物的抗逆转录病毒活性。最后，可以肯定的是，提出的工具可以快速，经济地识别潜在的抗逆转录病毒药物。