Multicomplex Pharmacophore Modeling of Estrogen Receptors Suggests the Probable Repurposing of Procaterol as an Antiproliferative Agent Against Breast Cancer Cells.

Breast cancer (BC) is a malignant tumor that develops in the mammary gland due to uncontrolled cell proliferation. Estrogen receptor (ER) signaling, mediated by 17β-estradiol (E2), plays a crucial role in regulating cell proliferation, differentiation, and survival. Specifically, the binding of E2 to the estrogen receptor alpha (ERα) increases cell proliferation. Conversely, selective estrogen receptor beta (ERβ) agonists inhibit cancer cell proliferation by suppressing the expression of oncogenes, making ERβ an important therapeutic target. Given the urgent need for targeted and effective therapies for BC, we implemented a strategy based on multicomplex pharmacophores modeling of ERβ (MPMERβ) and ERα (MPMERα), performing a virtual cross-screening of databases of clinically approved and experimental drugs to identify those with high affinity and stereoelectronic complementarity with the ERβ agonist pharmacophore hypothesis. The implementation of a chemoinformatic strategy enabled the identification of Sobetirome, Labetalol, and Procaterol as molecular hits on the ERβ pharmacophore map. Procaterol showed the most significant antiproliferative activity in vitro assays, with IC50 values of 21.26 and 36.10 µM in MCF-7 and MDA-MB-231, respectively. It is imperative to note that these findings require experimental validation of the ERβ activation pathways to strengthen the possible therapeutic repurposing of the drugs selected through our in silico approach. Finally, this strategy not only facilitates drug repurposing under in silico simulation but also provides valuable information for the rational design of new drugs against BC.