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

Somatic mutations of the Estrogen Receptor α (ERα) 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...

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Autores principales: Pavlin, Matic, Spinello, Angelo, Pennati, Marzia, Zaffaroni, Nadia, Gobbi, Silvia, Bisi, Alessandra, Colombo, Giorgio, Magistrato, Alessandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766519/
https://www.ncbi.nlm.nih.gov/pubmed/29330437
http://dx.doi.org/10.1038/s41598-017-17364-4
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author Pavlin, Matic
Spinello, Angelo
Pennati, Marzia
Zaffaroni, Nadia
Gobbi, Silvia
Bisi, Alessandra
Colombo, Giorgio
Magistrato, Alessandra
author_facet Pavlin, Matic
Spinello, Angelo
Pennati, Marzia
Zaffaroni, Nadia
Gobbi, Silvia
Bisi, Alessandra
Colombo, Giorgio
Magistrato, Alessandra
author_sort Pavlin, Matic
collection PubMed
description Somatic mutations of the Estrogen Receptor α (ERα) 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 µs) molecular dynamics simulations revealed that recurrent ERα polymorphisms (i. e. L536Q, Y537S, Y537N, D538G) (mERα) 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 the first 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 ERα isoforms, potentially allowing the community to move a step closer to ‘precision medicine’ calibrated on patients’ genetic profiles and disease progression.
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spelling pubmed-57665192018-01-17 A Computational Assay of Estrogen Receptor α Antagonists Reveals the Key Common Structural Traits of Drugs Effectively Fighting Refractory Breast Cancers Pavlin, Matic Spinello, Angelo Pennati, Marzia Zaffaroni, Nadia Gobbi, Silvia Bisi, Alessandra Colombo, Giorgio Magistrato, Alessandra Sci Rep Article Somatic mutations of the Estrogen Receptor α (ERα) 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 µs) molecular dynamics simulations revealed that recurrent ERα polymorphisms (i. e. L536Q, Y537S, Y537N, D538G) (mERα) 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 the first 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 ERα isoforms, potentially allowing the community to move a step closer to ‘precision medicine’ calibrated on patients’ genetic profiles and disease progression. Nature Publishing Group UK 2018-01-12 /pmc/articles/PMC5766519/ /pubmed/29330437 http://dx.doi.org/10.1038/s41598-017-17364-4 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Pavlin, Matic
Spinello, Angelo
Pennati, Marzia
Zaffaroni, Nadia
Gobbi, Silvia
Bisi, Alessandra
Colombo, Giorgio
Magistrato, Alessandra
A Computational Assay of Estrogen Receptor α Antagonists Reveals the Key Common Structural Traits of Drugs Effectively Fighting Refractory Breast Cancers
title A Computational Assay of Estrogen Receptor α Antagonists Reveals the Key Common Structural Traits of Drugs Effectively Fighting Refractory Breast Cancers
title_full A Computational Assay of Estrogen Receptor α Antagonists Reveals the Key Common Structural Traits of Drugs Effectively Fighting Refractory Breast Cancers
title_fullStr A Computational Assay of Estrogen Receptor α Antagonists Reveals the Key Common Structural Traits of Drugs Effectively Fighting Refractory Breast Cancers
title_full_unstemmed A Computational Assay of Estrogen Receptor α Antagonists Reveals the Key Common Structural Traits of Drugs Effectively Fighting Refractory Breast Cancers
title_short A Computational Assay of Estrogen Receptor α Antagonists Reveals the Key Common Structural Traits of Drugs Effectively Fighting Refractory Breast Cancers
title_sort computational assay of estrogen receptor α antagonists reveals the key common structural traits of drugs effectively fighting refractory breast cancers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766519/
https://www.ncbi.nlm.nih.gov/pubmed/29330437
http://dx.doi.org/10.1038/s41598-017-17364-4
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