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Comparison of electrotopological-state indices versus atomic charge and superdelocalisability indices in a QSAR study of the receptor binding properties of halogenated estradiol derivatives
journal contribution
posted on 2023-06-09, 03:26 authored by Taravat Ghafourian, M T CroninThe structural requirements for the binding of steroids to the oestrogen receptor (ER) are important both for the design of new drugs and to assess the health risks of chemicals with ER affinity. In the present QSAR study of receptor binding affinity (RBA) for estradiol derivatives, the atom-level electrotopological state indices have been compared with molecular orbital derived, atom-level parameters for superdelocalisability and atomic charge. The AM1 Hamiltonian was used to calculate molecular orbital parameters. The predictive power of the QSARs indicated that the superdelocalisability indices provide a better model than the electrotopological state indices, and that the atomic charges resulted in the highest prediction error. The most accurate predictions were achieved when other molecular descriptors were also employed in the construction of the QSAR.
History
Publication status
- Published
File Version
- Published version
Journal
Molecular DiversityISSN
1381-1991Publisher
Springer VerlagIssue
4Volume
8Page range
343-355Department affiliated with
- Biochemistry Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2017-11-30First Compliant Deposit (FCD) Date
2017-11-30Usage metrics
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No categories selectedKeywords
estradiol; estradiol derivative; estrogen receptor; ethinylestradiolaccuracy; article; atom; binding affinity; chemical parameters; comparative study; drug structure; halogenation; health hazard; prediction; priority journal; quantitative structure activity relation; receptor binding; risk assessmentAnimals; Electrophysiology; Estradiol; Estrogens; Least-Squares Analysis; ModelsChemical; Molecular Conformation; Molecular Structure; Protein Binding; Quantitative Structure-Activity Relationship; ReceptorsEstrogen; Regression Analysis; Reproducibility of Results; Steroids; Structure-Activity Relationship
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