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    https://scidar.kg.ac.rs/handle/123456789/19099| Title: | Human Estrogen Receptor α Antagonists. Part 1: 3-D QSAR-Driven Rational Design of Innovative Coumarin-Related Antiestrogens as Breast Cancer Suppressants through Structure-Based and Ligand-Based Studies | 
| Authors: | Mihović, Nezrina     Tomašević, Nevena     Matić, Sanja     Mitrović, Marina   Kostić, Danijela Sabatino, Manuela   Antonini, Lorenzo   Ragno, Rino   Mladenović, Milan | 
| Issue Date: | 2021 | 
| Abstract: | The estrogen receptor α (ERα) represents a 17β-estradiol-inducible transcriptional regulator that initiates the RNA polymerase II-dependent transcriptional machinery, pointed for breast cancer (BC) development via either genomic direct or genomic indirect (i.e., tethered) pathway. To develop innovative ligands, structure-based (SB) three-dimensional (3-D) quantitative structure-activity relationship (QSAR) studies have been undertaken from structural data taken from partial agonists, mixed agonists/antagonists (selective estrogen receptor modulators (SERMs)), and full antagonists (selective ERα downregulators (SERDs)) correlated with either wild-type or mutated ERα receptors. SB and ligand-based (LB) alignments allow us to rule out guidelines for the SB/LB alignment of untested compounds. 3-D QSAR models for ERα ligands, coupled with SB/LB alignment, were revealed to be useful tools to dissect the chemical determinants for ERα-based anticancer activity as well as to predict their potency. The herein developed protocol procedure was verified through the design and potency prediction of 12 new coumarin-based SERMs, namely, 3DQ-1a to 3DQ-1e, that upon synthesis turned to be potent ERα antagonists by means of either in vitro or in vivo assays (described in the second part of this study). | 
| URI: | https://scidar.kg.ac.rs/handle/123456789/19099 | 
| Type: | article | 
| DOI: | 10.1021/acs.jcim.1c00530 | 
| ISSN: | 1549-9596 | 
| SCOPUS: | 2-s2.0-85117841523 | 
| Appears in Collections: | Faculty of Medical Sciences, Kragujevac Faculty of Science, Kragujevac Institute for Information Technologies, Kragujevac | 
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Human Estrogen Receptor α Antagonists. Part 1 3‑D QSAR-Driven.pdf | 411.84 kB | Adobe PDF |  View/Open | 
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