Prediction of Ligand Binding Affinity and Orientation of Xenoestrogens to the Estrogen Receptor by Molecular Dynamics Simulations and the Linear Interaction Energy Method

Lipzig, Marola M.H. van; Laak, Antonius ter; Jongejan, Aldo; Vermeulen, Nico; Wamelink, Mirjam M. C.; Geerke, Daan P.; Meerman, John H.N.

doi:10.1021/jm0309607

Cited by 98 publications

(97 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An increasing number of structurally diverse estrogenic compounds have been identified and proposed as risk factors for disruption of reproductive development and tumorigenesis (23). Estrogenic chemicals are defined as substances, interacting and activating ER, which may interfere with the endocrine system (24).…”

mentioning

confidence: 99%

Dual Activities of Odorants on Olfactory and Nuclear Hormone Receptors

Pick

Etter

Baud

et al. 2009

Journal of Biological Chemistry

View full text Add to dashboard Cite

We have screened an odorant compound library and discovered molecules acting as chemical signals that specifically activate both G-protein-coupled olfactory receptors (ORs) on the cell surface of olfactory sensory neurons and the human nuclear estrogen receptor ␣ (ER) involved in transcriptional regulation of cellular differentiation and proliferation in a wide variety of tissues. Hence, these apparent dual active odorants induce distinct signal transduction pathways at different subcellular localizations, which affect both neuronal signaling, resulting in odor perception, and the ER-dependent transcriptional control of specific genes. We demonstrate these effects using fluorescence-based in vitro and cellular assays. Among these odorants, we have identified synthetic sandalwood compounds, an important class of molecules used in the fragrance industry. For one estrogenic odorant we have also identified the cognate OR. This prompted us to compare basic molecular recognition principles of odorants on the two structurally and apparent functionally non-related receptors using computational modeling in combination with functional assays. Faced with the increasing evidence that ORs may perform chemosensory functions in a number of tissues outside of the nasal olfactory epithelium, the unraveling of these molecular ligand-receptor interaction principles is of critical importance. In addition the evidence that certain olfactory sensory neurons naturally co-express ORs and ERs may provide a direct functional link between the olfactory and hormonal systems in humans. Our results are therefore useful for defining the structural and functional characteristics of ER-specific odorants and the role of odorant molecules in cellular processes other than olfaction.Our nose detects a large variety of odorant signals relying on about 350 different predicted G-protein-coupled olfactory receptors (ORs) 3 with a conserved seven-transmembrane helical structure (1-3). By binding odorant molecules ORs modulate the conversion of chemical into electrical neuronal signals that are finally decoded in higher brain regions to trigger emotional and behavioral responses (4 -6). Odorants are generally small, hydrophobic organic molecules with highly variable chemical structures and properties (7). They easily pass cell membranes, and, due to their enormous chemical diversity, some of them might, apart from their "conventional" role in olfaction, trigger also yet unknown cellular processes. The role of specific ORs in sperm chemotaxis has been documented (8,9), and the widespread ectopic expression of OR genes in a large number of non-olfactory human tissues implicates additional, unproven functions of ORs in embryonic development and cell-cell recognition (10), and proliferation rates in prostate cancer cells (11). Recent findings indicate that ORs might also have chemosensory functions in kidney (12). Although most present efforts concentrate on matching odorants with their cognate ORs to define their molecular receptive ranges and receptor fu...

show abstract

mentioning

confidence: 99%

Dual Activities of Odorants on Olfactory and Nuclear Hormone Receptors

Pick

Etter

Baud

et al. 2009

Journal of Biological Chemistry

View full text Add to dashboard Cite

show abstract

“…The system of choice is the ligand-binding domain (LBD) of the estrogen receptor (ER). Previous computational approaches to computing binding free energies for this system involve empirical regression-based methods (12)(13)(14), docking efforts (15), and free-energy calculations from molecular dynamics simulations (3,6,16). A great number of structurally diverse compounds have been shown to interact with the ER LBD (14,(17)(18)(19)(20)(21)(22)(23)(24).…”

mentioning

confidence: 99%

Free energies of ligand binding for structurally diverse compounds

Oostenbrink¹,

Gunsteren²

2005

Proc. Natl. Acad. Sci. U.S.A.

111

112

View full text Add to dashboard Cite

The one-step perturbation approach is an efficient means to calculate many relative free energies from a common reference compound. Combining lessons learned in previous studies, an application of the method is presented that allows for the calculation of relative binding free energies for structurally rather diverse compounds from only a few simulations. Based on the well known statistical-mechanical perturbation formula, the results do not require any empirical parameters, or training sets, only limited knowledge of the binding characteristics of the ligands suffices to design appropriate reference compounds. Depending on the choice of reference compound, relative free energies of binding rigid ligands to the ligand-binding domain of the estrogen receptor can be obtained that show good agreement with the experimental values. The approach presented here can easily be applied to many rigid ligands, and it should be relatively easy to extend the method to account for ligand flexibility. The free-energy calculations can be straightforwardly parallelized, allowing for an efficient means to understand and predict relative binding free energies. free-energy calculation ͉ molecular dynamics simulation ͉ estrogen receptor ͉ one-step perturbation T he calculation of relative binding free energies for several ligands to a common receptor is of relevance for drug design purposes, and for obtaining a better understanding of the molecular interactions of proteins with small compounds. Despite the increased availability of computational power, calculating free energies from molecular dynamics simulations is still time-consuming, often requiring several extensive simulations to obtain a single relative free energy. The approach in which several free energies can be obtained from a single simulation of a, not necessarily physically meaningful, reference state (1) has been applied successfully in recent years (2-6). The idea behind the method is to simulate a judiciously chosen reference compound R, generating an ensemble of structures that contains conformations representative for several physically relevant compounds. The free-energy difference between any real ligand A and the reference compound can be calculated from the perturbation formula (7)where the angle brackets indicate the ensemble average over the structures generated in a simulation of R. H A and H R are the Hamiltonians for the real compound (A) and the reference compound (R), respectively. Because this expression only involves the difference between the two Hamiltonians, only interactions that differ between compounds A and R need to be reevaluated over the ensemble. k B is the Boltzmann constant, and T is the temperature. As was demonstrated before, one can split up the process of changing the reference compound into a real ligand into insertion of a real ligand and the removal of the reference compound (6). Assuming that the removal of the reference compound is independent of the real ligand that was added, one can estimate the free-energy difference aswith G...

show abstract

“…3, ESA01-ESA10) used in this study was identical to that reported earlier. 27 In total, the database used for screening ligands against the ER-antagonist complex [Protein Data Bank (PDB) code: 3ert 26 ] and ER-agonist complex (PDB code: 1gwr 28 ) contained 1000 molecules; that is, 990 random compounds were the same for the 2 screens. In addition, 3 ER-antagonist complexes (PDB codes: 1err, 3ert, and 1hj1) and 4 ER-agonist complexes (PDB codes: 1gwr, 1l2i, 1qkm, and 3erd) with experimentally determined X-ray structures from the PDB were selected to evaluate not only the docking accuracy but also the pharmacological consensuses evolved from known active ligands (i.e., Figs.…”

Section: Preparations Of Ligand Databases and Target Proteinsmentioning

confidence: 99%

A pharmacophore‐based evolutionary approach for screening selective estrogen receptor modulators

Yang

Shen

2005

Proteins

View full text Add to dashboard Cite

We developed a pharmacophorebased evolutionary approach for virtual screening. This tool, termed the Generic Evolutionary Method for molecular DOCKing (GEMDOCK), combines an evolutionary approach with a new pharmacophorebased scoring function. The former integrates discrete and continuous global search strategies with local search strategies to expedite convergence. The latter, integrating an empirical-based energy function and pharmacological preferences (binding-site pharmacological interactions and ligand preferences), simultaneously serves as the scoring function for both molecular docking and postdocking analyses to improve screening accuracy. We apply pharmacological interaction preferences to select the ligands that form pharmacological interactions with target proteins, and use the ligand preferences to eliminate the ligands that violate the electrostatic or hydrophilic constraints. We assessed the accuracy of our approach using human estrogen receptor (ER) and a ligand database from the comparative studies of Bissantz et al. (J Med Chem 2000;43:4759 -4767). Using GEMDOCK, the average goodness-of-hit (GH) score was 0.83 and the average false-positive rate was 0.13% for ER antagonists, and the average GH score was 0.48 and the average false-positive rate was 0.75% for ER agonists. The performance of GEMDOCK was superior to competing methods such as GOLD and DOCK. We found that our pharmacophore-based scoring function indeed was able to reduce the number of false positives; moreover, the resulting pharmacological interactions at the binding site, as well as ligand preferences, were important to the screening accuracy of our experiments. These results suggest that GEMDOCK constitutes a robust tool for virtual database screening. Proteins 2005;59:205-220.

show abstract

Prediction of Ligand Binding Affinity and Orientation of Xenoestrogens to the Estrogen Receptor by Molecular Dynamics Simulations and the Linear Interaction Energy Method

Cited by 98 publications

References 50 publications

Dual Activities of Odorants on Olfactory and Nuclear Hormone Receptors

Dual Activities of Odorants on Olfactory and Nuclear Hormone Receptors

Free energies of ligand binding for structurally diverse compounds

A pharmacophore‐based evolutionary approach for screening selective estrogen receptor modulators

Contact Info

Product

Resources

About