Computer-Aided Ligand Discovery for Estrogen Receptor Alpha.

ABSTRACT: Breast cancer (BCa) is one of the most predominantly diagnosed cancers in women. Notably, 70% of BCa diagnoses are Estrogen Receptor ? positive (ER?+) making it a critical therapeutic target. With that, the two subtypes of ER, ER? and ER?, have contrasting effects on BCa cells. While ER? promotes cancerous activities, ER? isoform exhibits inhibitory effects on the same. ER-directed small molecule drug discovery for BCa has provided the FDA approved drugs tamoxifen, toremifene, raloxifene and fulvestrant that all bind to the estrogen binding site of the receptor. These ER-directed inhibitors are non-selective in nature and may eventually induce resistance in BCa cells as well as increase the risk of endometrial cancer development. Thus, there is an urgent need to develop novel drugs with alternative ER? targeting mechanisms that can overcome the limitations of conventional anti-ER? therapies. Several functional sites on ER?, such as Activation Function-2 (AF2), DNA binding domain (DBD), and F-domain, have been recently considered as potential targets in the context of drug research and discovery. In this review, we summarize methods of computer-aided drug design (CADD) that have been employed to analyze and explore potential targetable sites on ER?, discuss recent advancement of ER? inhibitor development, and highlight the potential opportunities and challenges of future ER?-directed drug discovery.

SUBMITTER: Bafna D 

PROVIDER: S-EPMC7352601 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature