+ Site Statistics
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Prediction of ligand binding affinity and orientation of xenoestrogens to the estrogen receptor by molecular dynamics simulations and the linear interaction energy method



Prediction of ligand binding affinity and orientation of xenoestrogens to the estrogen receptor by molecular dynamics simulations and the linear interaction energy method



Journal of Medicinal Chemistry 47(4): 1018-1030



Exposure to environmental estrogens has been proposed as a risk factor for disruption of reproductive development and tumorigenesis of humans and wildlife (McLachlan, J. A.; Korach, K. S.; Newbold, R. R.; Degen, G. H. Diethylstilbestrol and other estrogens in the environment. Fundam. Appl. Toxicol. 1984, 4, 686-691). In recent years, many structurally diverse environmental compounds have been identified as estrogens. A reliable computational method for determining estrogen receptor (ER) binding affinity is of great value for the prediction of estrogenic activity of such compounds and their metabolites. In the presented study, a computational model was developed for prediction of binding affinities of ligands to the ERalpha isoform, using MD simulations in combination with the linear interaction energy (LIE) approach. The linear interaction energy approximation was first described by Aqvist et al. (Aqvist, J.; Medina, C.; Samuelsson, J. E. A new method for predicting binding affinity in computer-aided drug design. Protein Eng. 1994, 7, 385-391) and relies on the assumption that the binding free energy (DeltaG) depends linearly on changes in the van der Waals and electrostatic energy of the system. In the present study, MD simulations of ligands in the ERalpha ligand binding domain (LBD) (Shiau, A. K.; Barstad, D.; Loria, P. M.; Cheng, L.; Kushner, P. J.; Agard, D. A.; Greene, G. L. The structural basis of estrogen receptor/coactivator recognition and the antagonism of this interaction by tamoxifen. Cell 1998, 95, 927-937), as well as ligands free in water, were carried out using the Amber 6.0 force field (http://amber.scripps.edu/). Contrary to previous LIE methods, we took into account every possible orientation of the ligands in the LBD and weighted the contribution of each orientation to the total binding affinity according to a Boltzman distribution. The training set (n = 19) contained estradiol (E2), the synthetic estrogens diethylstilbestrol (DES) and 11beta-chloroethylestradiol (E2-Cl), 16alpha-hydroxy-E2 (estriol, EST), the phytoestrogens genistein (GEN), 8-prenylnaringenin (8PN), and zearalenon (ZEA), four derivatives of benz[a]antracene-3,9-diol, and eight estrogenic monohydroxylated PAH metabolites. We obtained an excellent linear correlation (r(2) = 0.94) between experimental (competitive ER binding assay) and calculated binding energies, with K(d) values ranging from 0.15 mM to 30 pM, a 5 000 000-fold difference in binding affinity. Subsequently, a test set (n = 12) was used to examine the predictive value of our model. This set consisted of the synthetic estrogen 5,11-cis-diethyl-5,6,11,12-tetrahydrochrysene-2,8-diol (THC), daidzein (DAI), equol (EQU) and apigenin (API), chlordecone (KEP), progesterone (PRG), several mono- and dihydroxylated PAH metabolites, and two brominated biphenyls. The predicted binding affinities of these estrogenic compounds were in very good agreement with the experimental values (average deviation of 0.61 +/- 0.4 kcal/mol). In conclusion, our LIE model provides a very good method for prediction of absolute ligand binding affinities, as well as binding orientation of ligands.

Please choose payment method:






(PDF emailed within 0-6 h: $19.90)

Accession: 012438974

Download citation: RISBibTeXText

PMID: 14761204

DOI: 10.1021/jm0309607


Related references

Simulations of the estrogen receptor ligand-binding domain: affinity of natural ligands and xenoestrogens. Journal of Medicinal Chemistry 43(24): 4594-4605, 2000

Insights into ligand selectivity in estrogen receptor isoforms: molecular dynamics simulations and binding free energy calculations. Journal of Physical Chemistry. B 112(9): 2719-2726, 2008

Are automated molecular dynamics simulations and binding free energy calculations realistic tools in lead optimization? An evaluation of the linear interaction energy (LIE) method. Journal of Chemical Information and Modeling 46(5): 1972-1983, 2006

Ligand binding affinity prediction by linear interaction energy methods. Journal Of Computer-Aided Molecular Design. 12(1): 27-35,., 1998

What determines the van der Waals coefficient beta in the LIE (linear interaction energy) method to estimate binding free energies using molecular dynamics simulations?. Proteins 34(3): 395-402, 1999

Molecular dynamics simulations of the estrogen receptor ligand binding domain. Biophysical Journal 82(1 Part 2): 486a, 2002

Binding affinity prediction with different force fields: examination of the linear interaction energy method. Journal of Computational Chemistry 25(10): 1242-1254, 2004

New linear response method based on continuum solvent model for ligand-receptor binding affinity prediction. Abstracts of Papers American Chemical Society 222(1-2): COMP189, 2001

Evaluation of protein-ligand affinity prediction using steered molecular dynamics simulations. Journal of Biomolecular Structure and Dynamics 35(15): 3221-3231, 2017

Evaluation of several two-step scoring functions based on linear interaction energy, effective ligand size, and empirical pair potentials for prediction of protein-ligand binding geometry and free energy. Journal of Chemical Information and Modeling 51(9): 2047-2065, 2011

Applying linear interaction energy method for binding affinity calculations of podophyllotoxin analogues with tubulin using continuum solvent model and prediction of cytotoxic activity. Journal of Molecular Graphics and Modelling 27(8): 930-943, 2009

Prediction of protein-ligand binding affinity by free energy simulations: assumptions, pitfalls and expectations. Journal of Computer-Aided Molecular Design 24(8): 639-658, 2010

Activation helix orientation of the estrogen receptor is mediated by receptor dimerization: evidence from molecular dynamics simulations. Physical Chemistry Chemical Physics 17(20): 13403-13420, 2015

Molecular Dynamics Simulations of a Binding Intermediate between FKBP12 and a High-Affinity Ligand. Journal of Chemical Theory and Computation 7(3): 725-741, 2011

Ligand dissociation from estrogen receptor is mediated by receptor dimerization: evidence from molecular dynamics simulations. Molecular Endocrinology 22(7): 1565-1578, 2008