Aplicación del cribado virtual para la obtención de nuevos esteroides 17α-metilados con potencial actividad anabólica y androgénica.

Computational methods for virtual screening of large databases are taken into account in the use of models of biological structure-activity relationship (QSAR), which makes an interesting alternative for high-through put screening (SAR) as an important tool for drug discovery. In previous builds first QSAR model for prediction of new anabolic-androgenic a loose collection of molecules whose biological activity was previously evaluated in vivo. In this model it was used quantum molecular descriptors and chemical-physical, coupled with chemometric techniques that help explain how the steric, electronic and hydrophobic characteristics influence in the biological response of these compounds. In this paper it was use the model equation above and perform a virtual screening applied to anabolic- androgenic steroids synthesized and evaluated by the authors before, where it is shown that the model developed can be applied in the identification of new lead compounds with best anabolic activity. Because these results are designing an appropriate sequence for synthetic 17α-methyl steroids, which yielded five new compounds with potential anabolic activity, correctly characterized by 1H, 13C NMR spectroscopy and mass spectrometry. [ABSTRACT FROM AUTHOR]