Quantitative structure-activity relationship (QSAR) study with a series of 17α-derivatives of estradiol: Model for the development of reversible steroid sulfatase inhibitors

摘要

Steroid sulfatase (STS) is the steroidogenic enzyme responsible for the hydrolysis of different sulfated steroids into their corresponding hydroxylated forms. This enzyme attracts our attention for its potential role in the growth of hormone-dependent breast and prostate tumors by the transformation of inactive sulfated precursors (which are very abundant in the blood) into active sex steroids. In order to identify the parameters responsible for good affinity with the active enzyme site and thus producing a good reversible STS inhibitor, we have built a quantitative structure-activity relationship (QSAR) model by using MDL-QSAR software which analyzes the molecules through more than 400 molecular descriptors. A total of 65 derivatives in position 17α of estradiol with their corresponding IC50 values were used to create our QSAR model. The linear regression converged through an optimization process to a relatively simple equation described by 4 molecular descriptors (Log P, nelem, Κ0 and Κα3). Virtual screening of approximately 200 molecules then enabled us to direct the synthesis of new reversible STS inhibitors.