A Computational Assay of Estrogen Receptor alpha Antagonists Reveals the Key Common Structural Traits of Drugs Effectively Fighting Refractory Breast Cancers

作者：Pavlin Matic; Spinello Angelo; Pennati Marzia; Zaffaroni Nadia; Gobbi Silvia; Bisi Alessandra; Colombo Giorgio; Magistrato Alessandra^*

来源：Scientific Reports, 2018, 8(1): 649.

DOI：10.1038/s41598-017-17364-4

Somatic mutations of the Estrogen Receptor alpha (ER alpha) occur with an up to 40% incidence in ER sensitive breast cancer (BC) patients undergoing prolonged endocrine treatments. These polymorphisms are implicated in acquired resistance, disease relapse, and increased mortality rates, hence representing a current major clinical challenge. Here, multi-microseconds (12.5 mu s) molecular dynamics simulations revealed that recurrent ER alpha. polymorphisms (i.e. L536Q, Y5375, Y537N, D538G) (mER alpha) are constitutively active in their apo form and that they prompt the selection of an agonist (active)-like conformation even upon antagonists binding. Interestingly, our simulations rationalize, for thefirst time, the efficacy profile of (pre)clinically used Selective Estrogen Receptor Modulators/Downregulators (SERMs/SERDs) against these variants, enlightening, at atomistic level of detail, the key common structural traits needed by drugs able to effectively fight refractory BC types. This knowledge represents a key advancement for mechanism-based therapeutics targeting resistant ER alpha isoforms, potentially allowing the community to move a step closer to 'precision medicine' calibrated on patients' genetic profiles and disease progression.

• 出版日期2018-1-12