An extended aqueous solvation model based on atom-weighted solvent accessible surface areas: SAWSA v2.0 model

A new method is proposed for calculating aqueous solvation free energy based on atom-weighted solvent accessible surface areas. The method, SAWSA v2.0, gives the aqueous solvation free energy by summing the contributions of component atoms and a correction factor. We applied two different sets of atom typing rules and fitting processes for small organic molecules and proteins, respectively. For small organic molecules, the model classified the atoms in organic molecules into 65 basic types and additionally. For small organic molecules we proposed a correction factor of hydrophobic carbon to account for the aggregation of hydrocarbons and compounds with long hydrophobic aliphatic chains. The contributions for each atom type and correction factor were derived by multivariate regression analysis of 379 neutral molecules and 39 ions with known experimental aqueous solvation free energies. Based on the new atom typing rules, the correlation coefficient (r) for fitting the whole neutral organic molecules is 0.984, and the absolute mean error is 0.40 kcal mol^–1, which is much better than those of the model proposed by Wang et al. and the SAWSA model previously proposed by us. Furthermore, the SAWSA v2.0 model was compared with the simple atom-additive model based on the number of atom types (NA). The calculated results show that for small organic molecules, the predictions from the SAWSA v2.0 model are slightly better than those from the atom-additive model based on NA. However, for macromolecules such as proteins, due to the connection between their molecular conformation and their molecular surface area, the atom-additive model based on the number of atom types has little predictive power. In order to investigate the predictive power of our model, a systematic comparison was performed on seven solvation models including SAWSA v2.0, GB/SA_1, GB/SA_2, PB/SA_1, PB/SA_2, AM1/SM5.2R and SM5.0R. The results showed that for organic molecules the SAWSA v2.0 model is better than the other six solvation models. For proteins, the model classified the atoms into 20 basic types and the predicted aqueous free energies of solvation by PB/SA were used for fitting. The solvation model based on the new parameters was employed to predict the solvation free energies of 38 proteins. The predicted values from our model were in good agreement with those from the PB/SA model and were much better than those given by the other four models developed for proteins.Figure The definition of hydrophobic carbons. Here CA, CB and CD are three carbon atoms; X represents a heteroatom. According to our definition, CB is a hydrophobic carbon, CA is not a hydrophobic carbon because a heteroatom is within four atoms and CD is not a hydrophobic carbon because CD is sp²- hydridized and in a six-member ring.Electronic Supplementary Material Supplementary material is available for this article at     

Effects of solvent composition and ionic strength on the interaction of quinoline antimalarials with ferriprotoporphyrin IX

Enthalpy-entropy compensation in the interaction of quinoline antimalarials with ferriprotoporphyrin IX (Fe(III)PPIX) in 40% aqueous dimethyl sulfoxide (DMSO) has been compared with that in pure aqueous solution. The data indicate that the degree of desolvation and loss of conformational freedom is virtually identical in both systems. Taken together with previous findings showing that the molar free energies of association of these drugs with Fe(III)PPIX in both solvent systems are very similar, this suggests that the recognition site on the metalloporphyrin is comparable in both cases. This is despite the fact that Fe(III)PPIX exists as a dimer in aqueous solution, but is monomeric in 40% DMSO. Free energies of association of chloroquine, quinine and quinidine with Fe(III)PPIX are largely insensitive to the concentration of sodium perchlorate in 40% DMSO. This demonstrates that electrostatic interactions play only a minor role in the overall stability of these complexes under these conditions. Increasing DMSO concentration greatly weakens the interactions of chloroquine, amodiaquine, quinine, quinidine and 9-epiquinine with Fe(III)PPIX. This suggests that hydrophobic interaction plays a major role in the stability of these complexes. Further investigation of chloroquine has revealed that the free energy of association with Fe(III)PPIX also weakens as a function of decreasing solvent polarity in pure organic solvents. However, the free energies of association are weaker in the mixed aqueous solvent than in pure organic solvents. This indicates that dispersion and electrostatic interactions are relatively strong in the non-aqueous environment. The results demonstrate that any successful model of antimalarial drug-Fe(III)PPIX interactions will need to take both solvation and electrostatic factors into account.     

A CFF 91-based Continuum Solvation Model: Solvation Free Energies of Small Organic Molecules and Conformations of the Alanine Dipeptide in Solution

Abstract

For molecular mechanics simulations of solvated molecules, it is important to use a consistent approach for calculating both the force field energy and the solvation free energy. A continuum solvation model based upon the atomic charges provided with the CFF91 force field is derived. The electrostatic component of the solvation free energy is described by the Poisson-Bolzmann equation while the nonpolar comonent of the solvation energy is assumed to be proportional to the solvent accessible surface area of the solute. Solute atomic radii used to describe the interface between the solute and solvent are fitted to reproduce the energies of small organic molecules. Data for 140 compounds are presented and compared to experiment and to the results from the well-characterized quantum mechanical solvation model AM1-SM2. In particular, accurate results are obtained for amino acid neutral analogues (mean unsigned error of 0.3 kcal/mol). The conformational energetics of the solvated alanine dipeptide is discussed.     

The application of a 3D-QSAR (autoMEP/PLS) approach as an efficient pharmacodynamic-driven filtering method for small-sized virtual library: application to a lead optimization of a human A3 adenosine receptor antagonist

We have recently reported that the combination of molecular electrostatic potential (MEP) surface properties (autocorrelation vectors) with the conventional partial least squares (PLS) analysis can be used to produce a robust ligand-based 3D structure-activity relationship (autoMEP/PLS) for the prediction of the human A3 receptor antagonist activities. Here, we present the application of the 3D-QSAR (autoMEP/PLS) approach as an efficient and alternative pharmacodynamic filtering method for small-sized virtual library. For this purpose, a small-sized combinatorial library (841 compounds) was derived from the scaffold of the known human A3 antagonist pyrazolo-triazolo-pyrimidines. The most interesting analogues were further prioritized for synthesis and pharmacological characterization. Remarkably, we have found that all the newly synthetized compounds are correctly predicted as potent human A3 antagonists. In particular, two of them are correctly predicted as sub-nanomolar inhibitors of the human A3 receptor.     

Macromolecular solvation energies derived from small molecule crystal morphology.

The morphology of small molecule crystals provides a model for evaluating surface solvation energies in a system with similar packing density to that observed for amino acid residues in proteins. The solvation energies associated with the transfer of methylene and carboxyl groups between vacuum and aqueous phases are estimated to be approx. $40 and -260 cal/A2, respectively, from an analysis of the morphology of succinic acid crystals. These solvation energies predict values for contact angles in reasonable agreement with measurements determined from macroscopic monolayer surfaces. Transfer free energies between vapor and water phases for a series of carboxylic acids are also predicted reasonably well by these solvation energies, provided the surface exposure of different groups is quantitated with the molecular surface area rather than the more traditional accessible surface area. In general, molecular surfaces and molecular surface areas are seen to have important advantages for characterizing the structure and energetics of macromolecular surfaces. Crystal faces of succinic acid with the lowest surface energies in aqueous solution are characteristically smooth. Increasing surface roughness and apolarity are associated with higher surface energies, which suggests an approach for modifying the surface properties of proteins and other macromolecules.     

Comparison of end-point continuum-solvation methods for the calculation of protein-ligand binding free energies

We have compared the predictions of ligand‐binding affinities from several methods based on end‐point molecular dynamics simulations and continuum solvation, that is, methods related to MM/PBSA (molecular mechanics combined with Poisson–Boltzmann and surface area solvation). Two continuum‐solvation models were considered, viz., the Poisson–Boltzmann (PB) and generalised Born (GB) approaches. The nonelectrostatic energies were also obtained in two different ways, viz., either from the sum of the bonded, van der Waals, nonpolar solvation energies, and entropy terms (as in MM/PBSA), or from the scaled protein–ligand van der Waals interaction energy (as in the linear interaction energy approach, LIE). Three different approaches to calculate electrostatic energies were tested, viz., the sum of electrostatic interaction energies and polar solvation energies, obtained either from a single simulation of the complex or from three independent simulations of the complex, the free protein, and the free ligand, or the linear‐response approximation (LRA). Moreover, we investigated the effect of scaling the electrostatic interactions by an effective internal dielectric constant of the protein (?_int). All these methods were tested on the binding of seven biotin analogues to avidin and nine 3‐amidinobenzyl‐1H‐indole‐2‐carboxamide inhibitors to factor Xa. For avidin, the best results were obtained with a combination of the LIE nonelectrostatic energies with the MM+GB electrostatic energies from a single simulation, using ?_int = 4. For fXa, standard MM/GBSA, based on one simulation and using ?_int = 4–10 gave the best result. The optimum internal dielectric constant seems to be slightly higher with PB than with GB solvation. © Proteins 2012; © 2012 Wiley Periodicals, Inc.     

Experimental and theoretical studies on the molecular properties of ciprofloxacin,norfloxacin, pefloxacin,sparfloxacin, and gatifloxacin in determining bioavailability

The aim of this investigation is to identify, by in silico and in vitro methods, the molecular determinants, e.g., solubility in an aqueous medium and lipophilic properties, which have an effect on the bioavailability of five selected fluoroquinolones. These properties were estimated by analysis of the electrostatic potential pattern and values of free energy of solvation as well as the partition coefficients of the studied compounds. The study is based on theoretical quantum-chemical methods and a simple experimental shake-flask technique with two immiscible phases, n-octanol and phosphate buffer. The solvation free energy values of compounds in both environments appeared to be negative. The wide range of electrostatic potential from negative to positive demonstrates the presence of dipole–dipole intermolecular interactions, while the high electron density at various sites indicates the possibility of hydrogen bond formation with solvent molecules. High partition coefficient values, obtained by summing the atomic contributions, did not take various correction factors into account and therefore were not accurate. Theoretical partition coefficient values based on more accurate algorithms, which included these correction factors (fragmental methods), yielded more accurate values. Theoretical methods are useful tools for predicting the bioavailability of fluoroquinolones.     

Application of a universal solvation model to nucleic acid bases: comparison of semiempirical molecular orbital theory, ab initio Hartree-Fock theory, and density functional theory

The free energies of solvation of six nucleic acid bases (adenine, cytosine, hypoxanthine, guanine, thymine, and uracil) in water and chloroform are calculated using CM2 class IV charges and SM5.42R atomic surface tensions. Using any of three approximations to the electronic wave function (AM1, Hartree-Fock, or DFT), we obtain good agreement with experiment for five cases where the experimental results are known for the partition coefficients between the two solvents. Decomposition of the solvation effects into bulk electrostatic contributions and first-solvation-shell effects shows that the partitioning is dominated by the former, and this illustrates the importance of using accurate partial atomic charges for modeling these molecules in aqueous solution.     

Electrostatic potentials and electrostatic interaction energies of rat cytochrome b5 and a simulated anion-exchange adsorbent surface.

Electrostatic potentials were determined for the soluble tryptic core of rat cytochrome b5 (using a structure derived from homology modeling) and a simulated anion-exchange surface through application of the linearized finite-difference Poisson-Boltzmann equation with the simulation code UHBD. Objectives of this work included determination of the contributions of the various charged groups on the protein surface to electrostatic interactions with a simulated anion-exchange surface as a function of orientation, separation distance, and ionic strength, as well as examining the potential existence of a preferred contact orientation. Electrostatic interaction free energies for the complex of the model protein and the simulated surface were computed using the electrostatics section of UHBD employing a 110(3) grid. An initial coarse grid spacing of 2.0 A was required to obtain correct boundary conditions. The boundary conditions of the coarse grid were used in subsequent focusing steps until the electrostatic interaction free energies were relatively independent of grid spacing (at approximately 0.5 A). Explicit error analyses were performed to determine the effects of grid spacing and other model assumptions on the electrostatic interaction free energies. The computational results reveal the presence of a preferred interaction orientation; the interaction energy between these two entities, of opposite net charge, is repulsive over a range of orientations. The electrostatic interaction free energies appear to be the summation of multiple fractional interactions between the protein and the anion-exchange surface. The simulation results are compared with those of ion-exchange adsorption experiments with site-directed mutants of the recombinant protein. Comparisons of the results from the computational and experimental studies should lead to a better understanding of electrostatic interactions of proteins and charged surfaces.     

Accurate aqueous proton dissociation constants calculations for selected angiotensin-converting enzyme inhibitors

Studies that allow computing values of aqueous proton dissociation constants (pKa), gas phase proton affinities, and the free energy of solvation have been performed for six members of angiotensin-I-converting enzyme (ACE) inhibitor family (captopril, enalaprilat, imidaprilat, ramiprilat, perindoprilat, and spiraprilat). Density functional theory (DFT) calculations using PBE1PBE functional on optimized molecular geometries have been carried out to investigate the thermodynamics of gas-phase protonation. The conductor-like polarizable continuum model (CPCM) solvation method at various levels of theory was applied to calculate the free energy of solvation for the ACE inhibitors and their respective anions. The CPCM solvation calculations were performed on both gas-phase and solvent-phase optimized structures. The combination of gas-phase and solvation energies according to the thermodynamic cycle enabled us to compute accurate pKa values for the all studied molecules.     

Hydrophobic regions on protein surfaces. Derivation of the solvation energy from their area distribution in crystallographic protein structures.

For the first time, a direct approach for the derivation of an atomic solvation parameter from macromolecular structural data alone is presented. The specific free energy of solvation for hydrophobic surface regions of proteins is delineated from the area distribution of hydrophobic surface patches. The resulting value is 18 cal/(mol.A2), with a statistical uncertainty of +/-2 cal/mol.A2) at the 5% significance level. It compares favorably with the parameters for carbon obtained by other authors who use the the crystal geometry of succinic acid or energies of transfer from hydrophobic solvent to water for small organic compounds. Thus, the transferability of atomic solvation parameters for hydrophobic atoms to macromolecules has been directly demonstrated. A careful statistical analysis demonstrates that surface energy parameters derived from thermodynamic data of protein mutation experiments are clearly less confident.     

Accurate Aqueous Proton Dissociation Constants Calculations for Selected Angiotensin-Converting Enzyme Inhibitors

Abstract

Studies that allow computing values of aqueous proton dissociation constants (pK_a), gas phase proton affinities, and the free energy of solvation have been performed for six members of angiotensin-I-converting enzyme (ACE) inhibitor family (captopril, enalaprilat, imidaprilat, ramiprilat, perindoprilat, and spiraprilat). Density functional theory (DFT) calculations using PBE1PBE functional on optimized molecular geometries have been carried out to investigate the thermodynamics of gas-phase protonation. The conductor-like polarizable continuum model (CPCM) solvation method at various levels of theory was applied to calculate the free energy of solvation for the ACE inhibitors and their respective anions. The CPCM solvation calculations were performed on both gas-phase and solvent-phase optimized structures. The combination of gas-phase and solvation energies according to the thermodynamic cycle enabled us to compute accurate pK_a values for the all studied molecules.     

Amino acid conformational preferences and solvation of polar backbone atoms in peptides and proteins

Amino acids in peptides and proteins display distinct preferences for alpha-helical, beta-strand, and other conformational states. Various physicochemical reasons for these preferences have been suggested: conformational entropy, steric factors, hydrophobic effect, and backbone electrostatics; however, the issue remains controversial. It has been proposed recently that the side-chain-dependent solvent screening of the local and non-local backbone electrostatic interactions primarily determines the preferences not only for the alpha-helical but also for all other main-chain conformational states. Side-chains modulate the electrostatic screening of backbone interactions by excluding the solvent from the vicinity of main-chain polar atoms. The deficiency of this electrostatic screening model of amino acid preferences is that the relationships between the main-chain electrostatics and the amino acid preferences have been demonstrated for a limited set of six non-polar amino acid types in proteins only. Here, these relationships are determined for all amino acid types in tripeptides, dekapeptides, and proteins. The solvation free energies of polar backbone atoms are approximated by the electrostatic contributions calculated by the finite difference Poisson-Boltzmann and the Langevin dipoles methods. The results show that the average solvation free energy of main-chain polar atoms depends strongly on backbone conformation, shape of side-chains, and exposure to solvent. The equilibrium between the low-energy beta-strand conformation of an amino acid (anti-parallel alignment of backbone dipole moments) and the high-energy alpha conformation (parallel alignment of backbone dipole moments) is strongly influenced by the solvation of backbone polar atoms. The free energy cost of reaching the alpha conformation is by approximately 1.5 kcal/mol smaller for residues with short side-chains than it is for the large beta-branched amino acid residues. This free energy difference is comparable to those obtained experimentally by mutation studies and is thus large enough to account for the distinct preferences of amino acid residues. The screening coefficients gamma(local)(r) and gamma(non-local)(r) correlate with the solvation effects for 19 amino acid types with the coefficients between 0.698 to 0.851, depending on the type of calculation and on the set of point atomic charges used. The screening coefficients gamma(local)(r) increase with the level of burial of amino acids in proteins, converging to 1.0 for the completely buried amino acid residues. The backbone solvation free energies of amino acid residues involved in strong hydrogen bonding (for example: in the middle of an alpha-helix) are small. The hydrogen bonded backbone is thus more hydrophobic than the peptide groups in random coil. The alpha-helix forming preference of alanine is attributed to the relatively small free energy cost of reaching the high-energy alpha-helix conformation. These results confirm that the side-chain-dependent solvent screening of the backbone electrostatic interactions is the dominant factor in determining amino acid conformational preferences.     

Evaluation of the conformational free energies of loops in proteins

In this paper we discuss the problem of including solvation free energies in evaluating the relative stabilities of loops in proteins. A conformational search based on a gas-phase potential function is used to generate a large number of trial conformations. As has been found previously, the energy minimization step in this process tends to pack charged and polar side chains against the protein surface, resulting in conformations which are unstable in the aqueous phase. Various solvation models can easily identify such structures. In order to provide a more severe test of solvation models, gas phase conformations were generated in which side chains were kept extended so as to maximize their interaction with the solvent. The free energies of these conformations were compared to that calculated for the crystal structure in three loops of the protein E. coli RNase H, with lengths of 7, 8, and 9 residues. Free energies were evaluated with a finite difference Poisson-Boltzmann (FDPB) calculation for electrostatics and a surface area-based term for nonpolar contributions. These were added to a gas-phase potential function. A free energy function based on atomic solvation parameters was also tested. Both functions were quite successful in selecting, based on a free energy criterion, conformations quite close to the crystal structure for two of the three loops. For one loop, which is involved in crystal contacts, conformations that are quite different from the crystal structure were also selected. A method to avoid precision problems associated with using the FDPB method to evaluate conformational free energies in proteins is described. © 1994 John Wiley & Sons, Inc.     

Ligand solvation in molecular docking

Solvation plays an important role in ligand‐protein association and has a strong impact on comparisons of binding energies for dissimilar molecules. When databases of such molecules are screened for complementarity to receptors of known structure, as often occurs in structure‐based inhibitor discovery, failure to consider ligand solvation often leads to putative ligands that are too highly charged or too large. To correct for the different charge states and sizes of the ligands, we calculated electrostatic and non‐polar solvation free energies for molecules in a widely used molecular database, the Available Chemicals Directory (ACD). A modified Born equation treatment was used to calculate the electrostatic component of ligand solvation. The non‐polar component of ligand solvation was calculated based on the surface area of the ligand and parameters derived from the hydration energies of apolar ligands. These solvation energies were subtracted from the ligand‐receptor interaction energies. We tested the usefulness of these corrections by screening the ACD for molecules that complemented three proteins of known structure, using a molecular docking program. Correcting for ligand solvation improved the rankings of known ligands and discriminated against molecules with inappropriate charge states and sizes. Proteins 1999;34:4–16. © 1999 Wiley‐Liss, Inc.     

Description of hydration free energy density as a function of molecular physical properties

A method to calculate the solvation free energy density (SFED) at any point in the cavity surface or solvent volume surrounding a solute is proposed. In the special case in which the solvent is water, the SFED is referred to as the hydration free energy density (HFED). The HFED is described as a function of some physical properties of the molecules. These properties are represented by simple basis functions. The hydration free energy of a solute was obtained by integrating the HFED over the solvent volume surrounding the solute, using a grid model. Of 34 basis functions that were introduced to describe the HFED, only six contribute significantly to the HFED. These functions are representations of the surface area and volume of the solute, of the polarization and dispersion of the solute, and of two types of electrostatic interactions between the solute and its environment. The HFED is described as a linear combination of these basis functions, evaluated by summing the interaction energy between each atom of the solute with a grid point in the solvent, where each grid point is a representation of a finite volume of the solvent. The linear combination coefficients were determined by minimizing the error between the calculated and experimental hydration free energies of 81 neutral organic molecules that have a variety of functional groups. The calculated hydration free energies agree well with the experimental results. The hydration free energy of any other solute molecule can then be calculated by summing the product of the linear combination coefficients and the basis functions for the solute.     

Effective energy function for proteins in lipid membranes

A simple extension of the EEF1 energy function to heterogeneous membrane-aqueous media is proposed. The extension consists of (a) development of solvation parameters for a nonpolar phase using experimental data for the transfer of amino acid side-chains from water to cyclohexane, (b) introduction of a heterogeneous membrane-aqueous system by making the reference solvation free energy of each atom dependent on the vertical coordinate, (c) a modification of the distance-dependent dielectric model to account for reduced screening of electrostatic interactions in the membrane, and (d) an adjustment of the EEF1 aqueous model in light of recent calculations of the potential of mean force between amino acid side-chains in water. The electrostatic model is adjusted to match experimental observations for polyalanine, polyleucine, and the glycophorin A dimer. The resulting energy function (IMM1) reproduces the preference of Trp and Tyr for the membrane interface, gives reasonable energies of insertion into or adsorption onto a membrane, and allows stable 1-ns MD simulations of the glycophorin A dimer. We find that the lowest-energy orientation of melittin in bilayers varies, depending on the thickness of the hydrocarbon layer.     

Estimating protein-ligand binding free energy: atomic solvation parameters for partition coefficient and solvation free energy calculation

Solvation energy calculation is one of the main difficulties for the estimation of protein-ligand binding free energy and the correct scoring in docking studies. We have developed a new solvation energy estimation method for protein-ligand binding based on atomic solvation parameter (ASP), which has been shown to improve the power of protein-ligand binding free energy predictions. The ASP set, designed to handle both proteins and organic compounds and derived from experimental n-octanol/water partition coefficient (log P) data, contains 100 atom types (united model that treats hydrogen atoms implicitly) or 119 atom types (all-atom model that treats hydrogen atoms explicitly). By using this unified ASP set, an algorithm was developed for solvation energy calculation and was further integrated into a score function for predicting protein-ligand binding affinity. The score function reproduced the absolute binding free energies of a test set of 50 protein-ligand complexes with a standard error of 8.31 kJ/mol. As a byproduct, a conformation-dependent log P calculation algorithm named ASPLOGP was also implemented. The predictive results of ASPLOGP for a test set of 138 compounds were r = 0.968, s = 0.344 for the all-atom model and r = 0.962, s = 0.367 for the united model, which were better than previous conformation-dependent approaches and comparable to fragmental and atom-based methods. ASPLOGP also gave good predictive results for small peptides. The score function based on the ASP model can be applied widely in protein-ligand interaction studies and structure-based drug design.