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Hands-off linear interaction energy approach to binding mode and affinity estimation of estrogens
(2013)
With this work we target the development of a predictictive model for the identification of small molecules which bind to the estrogen receptor alpha and, thus, may act as endocrine disruptors. We propose a combined thermodynamic approach for the estimation of preferential binding modes along with corresponding free energy differences using a linear interaction energy (LIE) ansatz. The LIE model is extended by a Monte Carlo approach for the computation of conformational entropies as recently developed by our group. Incorporating the entropy contribution substantially increased the correlation with experimental affinity values. Both squared coefficients for the fitted data as well as the more meaningful leave-one-out cross-validation of predicted energies were elevated up to rFit2 = 0.87 and qLOO2 = 0.82, respectively. All calculations have been performed on a set of 31 highly diverse ligands regarding their structural properties and affinities to the estrogen receptor alpha. Comparison of predicted ligand orientations with crystallographic data retrieved from the Protein database pdb.org revealed remarkable binding mode predictions.
A novel approach for the simulation of host.guest systems by systematically scanning the host moleculefs orientations within the guest cavity is presented along with a thermodynamic strategy for determining preferential binding modes and corresponding optimal interaction energies between host and guest molecules. By way of example, the elution order of hexabromocyclododecane stereoisomers from high performance liquid chromatography separation on a permethylated β-cyclcodextrin stationary phase has been computed using classical molecular dynamics simulations with the explicit solvents water and acetonitrile. Comparison of estimated with experimental separation data reveals remarkable squared coefficients of correlation with R2=0.87 and a very high correlation RLOO2 . 0:72 using the leaveone-out cross-validation method and water as solvent. In particular, the approach presented shapes up as very robust in terms of the evaluated time range under consideration, reflecting well thermodynamic equilibria. These and further observations correlating with experimental results suggest the suitability of the underlying force fields and our multi-mode approach for the estimation of relative binding affinities for host–guest systems with unknown binding modes.