A comparison of progestin and androgen receptor binding using the CoMFA technique

Loughney, Deborah A.; Schwender, Charles F.

doi:10.1007/bf00126215

Cited by 43 publications

(31 citation statements)

References 7 publications

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“…Quantitative structure-activity relationship (QSAR) models and qualitative SAR approaches have had some success in identifying and depicting structural features that contribute to the ability of a chemical to interact with steroid hormones, for both the estrogen receptor (ER) (Anstead et al 1997;Fang et al 2001;McKinney and Waller 1994;Tong et al 1997aTong et al , 1997bTong et al , 1998Waller et al 1996b;Wiese and Brooks 1994) and the AR (Loughney and Schwender 1992;Mekenyan et al 1997;Singh et al 2000;Tucker et al 1988;Waller et al 1996a). In the case of environmentally occurring chemicals, studies have revealed a common pattern of steric and electronic features involved in molecular recognition and receptor binding affinity, in spite of the molecular diversity of such data sets.…”

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confidence: 99%

Interaction of organophosphate pesticides and related compounds with the androgen receptor.

Tamura

Yoshikawa

Gaido

et al. 2003

Environ Health Perspect

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Identification of several environmental chemicals capable of binding to the androgen receptor (AR) and interfering with its normal function has heightened concern about adverse effects across a broad spectrum of environmental chemicals. We previously demonstrated AR antagonist activity of the organophosphate (OP) pesticide fenitrothion. In this study, we characterized AR activity of analogues of fenitrothion to probe the structural requirements for AR activity among related chemicals. AR activity was measured using HepG2 human hepatoma cells transfected with human AR plus an androgen-responsive luciferase reporter gene, MMTV-luc. AR antagonist activity decreased as alkyl chain length of the phosphoester increased, whereas electron-donating properties of phenyl substituents of the tested compounds did not influence AR activity. Oxon derivatives of fenitrothion, which are more likely to undergo hydrolytic degradation, had no detectable AR antagonist activity. Molecular modeling results suggest that hydrogen-bond energies and the maximum achievable interatomic distance between two terminal H-bond capable sites may influence both the potential to interact with the AR and the nature of the interaction (agonist vs. antagonist) within this series of chemicals. This hypothesis is supported by the results of recent AR homology modeling and crystallographic studies relative to agonist- and antagonist-bound AR complexes. The present results are placed in the context of structure-activity knowledge derived from previous modeling studies as well as studies aimed toward designing nonsteroidal antiandrogen pharmaceuticals. Present results extend understanding of the structural requirements for AR activity to a new class of nonsteroidal, environmental, OP-related chemicals.

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confidence: 99%

Interaction of organophosphate pesticides and related compounds with the androgen receptor.

Tamura

Yoshikawa

Gaido

et al. 2003

Environ Health Perspect

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“…Several CoMFA models have been developed for both natural and synthetic estrogens (27-31) and for related steroids and their receptors (32)(33)(34). However, these studies either included limited structural diversity in the training set or were not validated with a test set.…”

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confidence: 99%

Quantitative structure-activity relationships (QSARs) for estrogen binding to the estrogen receptor: predictions across species.

Tong¹,

Perkins²,

Strelitz³

et al. 1997

Environ Health Perspect

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The recognition of adverse effects due to environmental endocrine disruptors in humans and wildlife has focused attention on the need for predictive tools to select the most likely estrogenic chemicals from a very large number of chemicals for subsequent screening and/or testing for potential environmental toxicity. A three-dimensional quantitative structure-activity relationship (QSAR) model using comparative molecular field analysis (CoMFA) was constructed based on relative binding affinity (RBA) data from an estrogen receptor (ER) binding assay using calf uterine cytosol. The model demonstrated significant correlation of the calculated steric and electrostatic fields with RBA and yielded predictions that agreed well with experimental values over the entire range of RBA values. Analysis of the CoMFA three-dimensional contour plots revealed a consistent picture of the structural features that are largely responsible for the observed variations in RBA. Importantly, we established a correlation between the predicted RBA values for calf ER and their actual RBA values for human ER. These findings suggest a means to begin to construct a more comprehensive estrogen knowledge base by combining RBA assay data from multiple species in 3D-QSAR based predictive models, which could then be used to screen untested chemicals for their potential to bind to the ER. Another QSAR model was developed based on classical physicochemical descriptors generated using the CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) program. The predictive ability of the CoMFA model was superior to the corresponding CODESSA model.ImagesFigure 2.Figure 3.Figure 4.Figure 5.

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“…Each conformation is taken in turn, and the molecular fields around it are calculated. The capabilities of the method and application of the derived models have been published in a number of papers (Loughney et al [13], Waller et al [14], Hong et al [15]). …”

Section: Introductionmentioning

confidence: 98%

Androgen receptor binding affinity: a QSAR evaluation

Todorov

Mombelli

Aı̈t-Aı̈ssa

et al. 2011

SAR and QSAR in Environmental Research

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The multiparameter formulation of the COmmon REactivity PAttern (COREPA) approach has been used to describe the structural requirements for eliciting rat androgen receptor (AR) binding affinity, accounting for molecular flexibility. Chemical affinity for AR binding was related to the distances between nucleophilic sites and structural features describing electronic and hydrophobic interactions between the receptor and ligands. Categorical models were derived for each binding affinity range in terms of specific distances, local (maximal donor delocalizability associated with the oxygen atom of the A ring), global nucleophilicity (partial positive surface areas and energy of the highest occupied molecular orbital) and hydrophobicity (log Kow) of the molecules. An integral screening tool for predicting binding affinity to AR was constructed as a battery of models, each associated with different activity bins. The quality of the screening battery of models was assessed using a high value (0.9) of the Pearson contingency coefficient. The predictability of the model was assessed by testing the model performance on external validation sets. A recently developed technique for selection of potential androgenically active chemicals was used to test the performance of the model in its applicability domain. Some of the selected chemicals were tested for AR transcriptional activation. The experimental results confirmed the theoretical predictions.

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A comparison of progestin and androgen receptor binding using the CoMFA technique

Cited by 43 publications

References 7 publications

Interaction of organophosphate pesticides and related compounds with the androgen receptor.

Interaction of organophosphate pesticides and related compounds with the androgen receptor.

Quantitative structure-activity relationships (QSARs) for estrogen binding to the estrogen receptor: predictions across species.

Androgen receptor binding affinity: a QSAR evaluation

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