An empirical method to calculate average molecular polarizabilities from the dependence of effective atomic polarizabilities on net atomic charge

Barron

2017

PLoS ONE

The flexible hydrophobic ligand binding pocket (LBP) of estrogen receptor α (ERα) allows the binding of a wide variety of endocrine disruptors. Upon ligand binding, the LBP reshapes around the contours of the ligand and stabilizes the complex by complementary hydrophobic interactions and specific hydrogen bonds with the ligand. Here we present a framework for quantitative analysis of the steric and electronic features of the human ERα-ligand complex using three dimensional (3D) protein-ligand interaction description combined with 3D-QSAR approach. An empirical hydrophobicity density field is applied to account for hydrophobic contacts of ligand within the LBP. The obtained 3D-QSAR model revealed that hydrophobic contacts primarily determine binding affinity and govern binding mode with hydrogen bonds. Several residues of the LBP appear to be quite flexible and adopt a spectrum of conformations in various ERα-ligand complexes, in particular His524. The 3D-QSAR was combined with molecular docking based on three receptor conformations to accommodate receptor flexibility. The model indicates that the dynamic character of the LBP allows accommodation and stable binding of structurally diverse ligands, and proper representation of the protein flexibility is critical for reasonable description of binding of the ligands. Our results provide a quantitative and mechanistic understanding of binding affinity and mode of ERα agonists and antagonists that may be applicable to other nuclear receptors.

Section: Methodsmentioning

confidence: 99%

Structure-Based Understanding of Binding Affinity and Mode of Estrogen Receptor α Agonists and Antagonists

Barron

2017

PLoS ONE

“…The MAE and R 2 of the organic compounds were 0.33 log units and 0.94, respectively. The model predicts the values well for most of the 601 organic compounds; however, 20 molecules, including sulfonamides and multihalogenated compounds, were predicted with absolute error lager than 1.0 log units because of inaccuracy of q i for these molecules (54,55).…”

Section: Calculation Of Partition Coefficients Of Organic Compounds Andmentioning

confidence: 95%

“…r ik is the distance between the ith atom and the kth surface fragment. The net atomic charge q i and the effective atomic polarizability α i of the ith atom of the solute were calculated by using the modified partial equalization of orbital electronegativity and the charge dependent effective atomic polarizability methods, respectively (51)(52)(53)(54)(55). The cavity surface of a solute is defined by the union of the SAS of atoms in the solute (Fig.…”

Section: Theorymentioning

confidence: 99%

“…The parameters for calculating q i and α i of the solute and those describing the cavity surface were taken from our previous work (46)(47)(48)(49)(50)(51)(52)(53)(54)(55), and only 12 empirical parameters were determined by minimizing the difference between calculated (ΔG cal solv ) and experimental (ΔG exp solv ) solvation free energies. The optimized 12 empirical parameters and the contribution of each basis function to ΔG solv are given in Table 1 and Table S2.…”

Section: Theorymentioning

confidence: 99%

See 1 more Smart Citation

A generalized G-SFED continuum solvation free energy calculation model

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

Cho

Kang

et al. 2013

Self Cite

An empirical continuum solvation model, solvation free energy density (SFED), has been developed to calculate solvation free energies of a molecule in the most frequently used solvents. A generalized version of the SFED model, generalized-SFED (G-SFED), is proposed here to calculate molecular solvation free energies in virtually any solvent. G-SFED provides an accurate and fast generalized framework without a complicated description of a solution. In the model, the solvation free energy of a solute is represented as a linear combination of empirical functions of the solute properties representing the effects of solute on various solute-solvent interactions, and the complementary solvent effects on these interactions were reflected in the linear expansion coefficients with a few solvent properties. G-SFED works well for a wide range of sizes and polarities of solute molecules in various solvents as shown by a set of 5,753 solvation free energies of diverse combinations of 103 solvents and 890 solutes. Octanol-water partition coefficients of small organic compounds and peptides were calculated with G-SFED with accuracy within 0.4 log unit for each group. The G-SFED computation time depends linearly on the number of nonhydrogen atoms (n) in a molecule, O(n).implicit solvent | macromolecules | linear time A n accurate description of the effect of solvent on solvation is crucial for understanding chemical and biological phenomena. Because many peptide and protein drugs are currently being developed (1, 2), computational efficiency as well as accuracy are very important. Among the different approaches that have been used, continuum solvation models are appealing because of the simplified yet accurate description of the solvent effect (3-8).Continuum solvent models have been developed based on the early work of Born (9), Bell (10), Kirkwood (11), and Onsanger (12). They focus primarily on the description of the solute either at the quantum mechanical level or as a classical collection of point charges and try to represent the influence of the solvent based on an approximate treatment as a dielectric continuum medium. The charge distribution of the solute induces electric polarization of the surrounding solvent, and the electric field generated by the polarized solvent, the reaction field, in turn perturbs the solute, leading to a modification of the charge distribution of the solute. This electrostatic problem of the mutual polarization between solute and solvent can be recast by using boundary conditions at the cavity surface, leading to significant simplifications in the associated equations.In the classical approaches, most work is concerned with describing the electrostatic contribution to the solvation in terms of the Poisson-Boltzmann equation (PBE) (13). Several different computational techniques for solving the PBE have been developed, for example, finite difference methods in which the dielectric property of the solvent is described in terms of a 3D grid around the solute (14-17) and boundary element methods i...

“…Atom-centered net atomic charges, q i , were calculated with an empirical net atomic charge calculation method, the modified part ial e qualizatio n of orbi tal e lectronegati vity (MPEOE), 18,19 and effective atomic polarizabilities, α i , were calculated using an empirical method, the charge dependent effective atomic polarizability (CDEAP). 20 The hydrogen bond stabilization term, ΔG HB , was divided into two terms on the basis of the role of the solvent in hydrogen bonding, with the acceptor and donor represented with the subscripts "a" and "d", respectively. These two terms were simple functions of the hydrogen bond acidity and basicity of the solute, A solute and B solute , respectively.…”

Section: ■ Methodologymentioning

confidence: 99%

Development of Surface-SFED Models for Polar Solvents

Cho

Acree

et al. 2012

J. Chem. Inf. Model.

Self Cite

We developed surface grid-based solvation free energy density (Surface-SFED) models for 36 commonly used polar solvents. The parametrization was performed with a large and diverse set of experimental solvation free energies mainly consisting of combinations of polar solvent and multipolar solute. Therefore, the contribution of hydrogen bonds was dominant in the model. In order to increase the accuracy of the model, an elaborate version of a previous hydrogen bond acidity and basicity prediction model was introduced. We present two parametrizations for use with experimentally determined (Surface-SFED/HB exp ) and empirical (Surface-SFED/HB cal ) hydrogen bond acidity and basicity values. Our computational results agreed well with experimental results, and inaccuracy of empirical hydrogen bond acidity and basicity values was the main source of error in Surface-SFED/HB cal . The mean absolute errors of Surface-SFED/HB exp and Surface-SFED/HB cal were 0.49 and 0.54 kcal/mol, respectively. ■ INTRODUCTIONSolvation effect plays an important role in a wide variety of phenomena in chemical and biological processes. The free energy of solvation of a solute is a fundamental quantity that represents the effect of solvation. Differences in the solvation free energies of a solute in immiscible solvents can be used to predict the partitioning of the solute between these solvents. For this reason, the development of models to calculate solvation free energies for diverse solvents may contribute much to the fields of computational biology and physical and biophysical chemistry.Because of the complexity of solute−solvent interactions, prediction of the solvation free energy is considered as one of the most challenging energy terms to calculate. Though many computational models have been proposed, from detailed ab initio models to fast empirical models, 1−8 most have so far been applied to a limited number of solvents, such as 1-octanol, chloroform, and particularly water. 9−13The solvation free energy density (SFED) model, an empirical continuum solvation model proposed by No et al., was developed to predict solvation free energies.14 The model has been applied to calculate solvation free energies in 10 solvents including water and 1-octanol, 14−16 to compute 1-octanol/ water partition coefficients, 15 and to generate the hydration free energy density tensor. 17 In a recent paper, 16 we extensively modified this model, as follows: (1) A basis function for electrostatics was modified to include ionic molecules. (2) Two basis functions were introduced to express hydrogen bond contributions. (3) A surface grid was introduced, instead of the shell grid, to avoid the bumping of the grid between molecules and improve computational efficiency. The parametrization was performed for over 10 solvents that have more than 50 solvation free energies, and the mean absolute errors (MAEs) for 1200 solvation free energies of 379 neutral molecules in these 10 solvents and 90 hydration free energies of ionics were 0.40 and 1.70 kcal/mol, ...