Projects
24: Internet application for the estimation of the binding affinity of small molecules towards the estrogen receptor in silico.
In silico modelling of the estrogen receptor.
The testing of adverse effects of potential endocrine disruptors in vitro and in vivo is highly time- and resource-consuming. Here, a computational tool will be developed to allow reliable prediction of the binding affinity of any small molecule to the estrogen receptor in silico and, subsequently, estimation of the endocrine-disrupting effect.
Vedani Angelo, Biographics Laboratory 3R, Basel
e-mail: angelo@biograf.ch
Background
Estrogens are involved in the growth, development and homeostasis of a number of tissues. The physiological effects of these steroids are mediated by the estrogen receptor (ER). The binding of xenobiotics to the ER triggers a series of molecular events responsible for the activation or repression of target genes, leading to undesired effects. It would therefore be extremely interesting to have a computational tool to enable fast and reliable estimation of the binding affinity of a given compound to the ER.
Our laboratory contributes to the in silico quantification of small–molecule protein interactions by devising molecular modelling concepts. As part of a larger project aimed at the prediction of adverse effects triggered by drugs and chemicals, we recently compiled a small database including five receptors known to mediate toxic phenomena, individually validated using large data sets using multi–dimensional QSAR (receptor modelling). This pilot system is able to predict both the known toxicity of compounds and the benign character of currently available drugs.
Aim
The aim of the project is to develop and validate a 3D model of the estrogen receptor which allows reliable prediction of the binding affinity of any small molecule and subsequently an estimation of its endocrine-disrupting effect. This technology will be made available to all Swiss universities, hospitals and regulatory bodies through an internet portal.
Significance
Our in silico technology does not require any ligand to be physically present (i.e. synthesized). Hence, any hypothetical or existing compound can quickly be scanned for potential activity towards the estrogen receptor. The method allows reliable prediction of the binding affinity of any molecule to the estrogen receptor. This simulation of ligand binding to the estrogen receptor could contribute to a further reduction in resources, waste and animal testing by timely elimination of undesirable candidates.
Our first results with 106 compounds from different molecular classes support the philosophy of using 3D receptor surrogates to quantitatively predict the binding affinity of hypothetical and existing molecules binding to the estrogen receptor.