Identification of the Estrogen Receptor (ER) as a key mediator of the proliferation of breast cancer, and its involvement in pathways leading to osteoporosis and coronary heart disease, has resulted in a surge to discover and design compounds with the ability to modulate its actions (SERMs). Concurrently, a dramatic increase in the number of crystal structures of the ER has led to a more in depth understanding of the governing mechanisms involved in ER modulation. Entwining computational techniques with the availability of 3D structural data, has allowed not only the rational design of potent inhibitors of the ER, but also its incorporation in Virtual Screening (VS) in the search for novel chemotypes that can modulate the ER. An important initial step in the VS process is to filter towards molecules that occupy similar chemical space to a set of known actives prior to docking. We illustrate through Principal Component Analysis (PCA) of 145 descriptors the region of chemical space antiestrogens occupy compared with drug-like space. We also review all available studies involving validation of several docking algorithms utilizing the ER, ultimately focusing on analysis of Enrichment (E) rates and False Positive (FP) rates to illustrate the successes attributed to each docking algorithm. Finally, we relate the recent discovery of non-genomic mechanisms of the ER and subsequently present a model involving a recently identified alternative, second binding-pocket of the ER in our laboratory through cavity analysis that suggests how the same receptor can invoke these, classical and rapid responses concurrently.
Keywords: Virtual screening, drug discovery, ER, SERMS, non-genomic, PCA, docking
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