Grant: CIHR Fellowship

26,000 Canadian women are diagnosed with breast cancer (BCa) and 5,000 die from it every year[1]. All current BCa drugs block estradiol binding to estrogen receptor alpha (ERa) directly or indirectly. While anti-estrogens are very effective in initially controlling advanced metastatic BCa, tumor cells eventually progress to a hormone-resistant state where they no longer respond to conventional treatments. The Activation Function-2 (AF2) site of ERa is a new promising therapeutic target for advanced BCas, as AF2 inhibitors would be effective in hormone-resistant forms, and mutations of the estradiol binding site should not affect their efficacy. We previously developed AF2 inhibitors able to suppress the growth of resistant BCa cells[2,3]. Herein we propose to expand on our preliminary results and identify better drug candidates for BCa. The number of small molecules available for screening has increased exponentially in the last few years, with major chemical databases already exceeding a billion of purchasable entries. Despite the immense potential for drug discovery offered by this surge of chemicals, research has been lagging behind due to the unavailability of methods able to deal with such enormous amount of data. We developed progressive docking (PD), an artificial intelligence method capable to increase the speed of virtual screening by above 50X[4], allowing to evaluate for the first time billions of molecules. We will use PD to screen the entire ZINC15 database, containing 1.3 billion compounds, to discover new potent AF2 inhibitors with optimized drug-like profiles. We anticipate that this study will yeald a class of therapeutics with a novel mechanism of action to improve the outcome of resistant BCa for patients in Canada and worldwide. References 1 Canadian Cancer Society. (2018) 2 Singh, K. et al. Breast Cancer Res. 17, 27 (2015) 3 Singh, K. et al. Int. J. Mol. Sci. 19, 579 (2018) 4 Agrawal, V. et al. in ICANN 2019, 737-740 (Springer, Cham, 2019)