QSAR models for estrogen binding to α and β estrogen receptors

Weida Tong; Roger Perkins; Li Xing; William J. Welsh; Daniel M. Sheehan

QSAR models for estrogen binding to α and β estrogen receptors

Weida Tong, Roger Perkins, Li Xing, William J. Welsh, Daniel M. Sheehan

Research output: Contribution to journal › Article › peer-review

Abstract

We have developed Quantitative Structure-Activity Relationship (QSAR) models based on Comparative Molecular Field Analysis (CoMFA) for 31 estrogenic chemicals whose relative binding affinity (RBA) is available for both ER-α and ER-β. The models demonstrated a significant correlation (r²>0.95) between the CoMFA-calculated steric/electrostatic fields and corresponding RBA data and a good predictive capability (r²>0.6) based on cross-validation. The CoMFA models and contour plots obtained for ER-α and ER-β suggest a close similarity between the receptors in terms of mode of binding and provide a rational basis for ligand selectivity.

Original language	English (US)
Pages (from-to)	4-7
Number of pages	4
Journal	ACS Division of Environmental Chemistry, Preprints
Volume	37
Issue number	2
State	Published - 1997
Externally published	Yes

All Science Journal Classification (ASJC) codes

General Chemical Engineering

Cite this

@article{588051b75a1046389095c172f98bb1b4,

title = "QSAR models for estrogen binding to α and β estrogen receptors",

abstract = "We have developed Quantitative Structure-Activity Relationship (QSAR) models based on Comparative Molecular Field Analysis (CoMFA) for 31 estrogenic chemicals whose relative binding affinity (RBA) is available for both ER-α and ER-β. The models demonstrated a significant correlation (r2>0.95) between the CoMFA-calculated steric/electrostatic fields and corresponding RBA data and a good predictive capability (r2>0.6) based on cross-validation. The CoMFA models and contour plots obtained for ER-α and ER-β suggest a close similarity between the receptors in terms of mode of binding and provide a rational basis for ligand selectivity.",

author = "Weida Tong and Roger Perkins and Li Xing and Welsh, {William J.} and Sheehan, {Daniel M.}",

year = "1997",

language = "English (US)",

volume = "37",

pages = "4--7",

journal = "ACS Division of Environmental Chemistry, Preprints",

issn = "0093-3066",

publisher = "American Chemical Society",

number = "2",

}

TY - JOUR

T1 - QSAR models for estrogen binding to α and β estrogen receptors

AU - Tong, Weida

AU - Perkins, Roger

AU - Xing, Li

AU - Welsh, William J.

AU - Sheehan, Daniel M.

PY - 1997

Y1 - 1997

N2 - We have developed Quantitative Structure-Activity Relationship (QSAR) models based on Comparative Molecular Field Analysis (CoMFA) for 31 estrogenic chemicals whose relative binding affinity (RBA) is available for both ER-α and ER-β. The models demonstrated a significant correlation (r2>0.95) between the CoMFA-calculated steric/electrostatic fields and corresponding RBA data and a good predictive capability (r2>0.6) based on cross-validation. The CoMFA models and contour plots obtained for ER-α and ER-β suggest a close similarity between the receptors in terms of mode of binding and provide a rational basis for ligand selectivity.

AB - We have developed Quantitative Structure-Activity Relationship (QSAR) models based on Comparative Molecular Field Analysis (CoMFA) for 31 estrogenic chemicals whose relative binding affinity (RBA) is available for both ER-α and ER-β. The models demonstrated a significant correlation (r2>0.95) between the CoMFA-calculated steric/electrostatic fields and corresponding RBA data and a good predictive capability (r2>0.6) based on cross-validation. The CoMFA models and contour plots obtained for ER-α and ER-β suggest a close similarity between the receptors in terms of mode of binding and provide a rational basis for ligand selectivity.

UR - http://www.scopus.com/inward/record.url?scp=5244334766&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=5244334766&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:5244334766

SN - 0093-3066

VL - 37

SP - 4

EP - 7

JO - ACS Division of Environmental Chemistry, Preprints

JF - ACS Division of Environmental Chemistry, Preprints

IS - 2

ER -

QSAR models for estrogen binding to α and β estrogen receptors

Abstract

All Science Journal Classification (ASJC) codes

Other files and links

Fingerprint

Cite this