Prostate cancer is one of the most common form of cancer among men, and its incidence has been increasing progressively. Since the prostate depends on androgenic hormones to regulate its growth and development, interference with androgenic biosynthesis are important to control the disease. Thus, in this work, a 4D-quantitative structure-activity relationship (QSAR) receptor independent study was carried out using the Laboratório de Quimiometria Teórica e Aplicada (LQTA)-QSAR approach and the new tool Web-4D-QSAR with a set of benzylidene oxazolidinedione and thiazolidinedione inhibitor of the 17β-hydroxysteroid dehydrogenase type 3. The obtained model is robust, free from chance correlation, and with good predictability in all tests performed. In addition to this result, a good mecanistic interpretation related to the binding with the biological target could be traced, which strengthens its potential application in virtual screening and design of new inhibitors of the studied enzyme with the possibility of use in the pharmacological treatment of prostate cancer.

QSAR modeling is a novel computer program developed to generate and validate QSAR or QSPR (quantitative structure- activity or property relationships) models. With QSAR modeling, users can build partial least squares (PLS) regression models, perform variable selection with the ordered predictors selection (OPS) algorithm, and validate models by using y-randomization and leave-N-out cross validation. An additional new feature is outlier detection carried out by simultaneous comparison of sample leverage with the respective Studentized residuals. The program was developed using Java version 6, and runs on any operating system that supports Java Runtime Environment version 6. The use of the program is illustrated. This program is available for download at lqta.iqm.unicamp.br.