## Abstract Estrogen‐responsive genes often have an estrogen response element (ERE) positioned next to activator protein‐1 (AP‐1) binding sites. Considering that the interaction between ERE and AP‐1 elements has been described for the modulation of bone‐specific genes, we investigated the 17‐β‐estr
New computational strategy to analyze the interactions of ERα and ERβ with different ERE sequences
✍ Scribed by Anna Marabotti; Giovanni Colonna; Angelo Facchiano
- Book ID
- 102306013
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 471 KB
- Volume
- 28
- Category
- Article
- ISSN
- 0192-8651
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✦ Synopsis
Abstract
The importance of computational methods for the simulation and analysis of biological systems has increased during the last years. In particular, methods to predict binding energies are developing not only with the aim of ranking the affinities between two or more complexes, but also to quantify the contribution of different types of interaction. In this work, we present the application of HINT, a non Newtonian force field, to rank the affinities of complexes formed by estrogen receptors (ER) α and β and different estrogen responsive elements (ERE) near the estrogen‐regulated genes. We used the crystallographic coordinates of the DNA binding domain of ERα complexed to a consensus ERE as a starting point to simulate several complexes in which some nucleotides in the ERE sequence were mutated. Moreover, we used homology modeling methods to create the structure of the complexes between the DNA binding domain of ERβ (for which no experimental structures are currently available) and the same ERE sequences. Our results show that HINT is able to rank the affinities of ERα and ERβ for different ERE sequences, and to correctly identify the positions on the DNA sequence that are most important for binding affinity. Moreover, the HINT output gives us the opportunity to identify and quantify the role played by each single atom of amino acids and nucleotides in the binding event, as well as to predict the effect on the binding affinity for other nucleotide mutations. © 2007 Wiley Periodicals, Inc. J Comput Chem 2007
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