4.7 Article

A computational study of potent series of selective estrogen receptor degraders for breast cancer therapy

Journal

Publisher

TAYLOR & FRANCIS INC
DOI: 10.1080/07391102.2022.2159877

Keywords

ADME predictions; global reactivity descriptors; molecular docking; molecular dynamics; PLS regression; Quantitative Structure-Activity Relationship (QSAR); SERDs

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This study provides a detailed investigation of the interaction between Selective Estrogen Receptor Down-Regulators (SERDs) and Estrogen Receptor alpha (ER alpha) using various methods including quantitative structure-activity relationship, molecular docking, and molecular dynamics simulation. The study establishes an empirical model with better predictive capability and explores the binding mechanism between the compounds and ER alpha. The findings contribute to predicting the anticancer activities of the SERD compounds and improving our understanding of their action mechanism with ER alpha.
A detailed multistep framework combining quantitative structure-activity relationship, global reactivity, absorption, distribution, metabolism and elimination properties, molecular docking and molecular dynamics simulation (MD) on a series of Selective Estrogen Receptor Down-Regulators (SERDs) interacting with Estrogen Receptor alpha (ER alpha) has been performed. The partial least squares regression method derived an empirical model with better predictive capability. The results of global reactivity descriptors revealed that all the compounds are considered strong electrophiles, allowing them to participate in polar reactions more easily. The Brain Or IntestinaL EstimateD permeation diagram revealed that compounds 49 and 31 were predicted to be well absorbed by the human gastrointestinal tract and would not enter the brain. The elucidation of the binding mode between the most active compounds that comply with Lipinski's and Veber's rules from the dataset and ER alpha targets was explored by molecular docking. The MD simulations were performed for 100 ns on the best compounds, which indicated their stability state under dynamics simulations. These findings are expected to help predict the anticancer activities of the studied SERD compounds and better understand their binding mechanism with ER alpha targets.Communicated by Ramaswamy H. Sarma

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