A “Universal” Surface Area Correlation for Molecular Hydrophobic Phenomena

CHARMM-GUI Implicit Solvent Modeler for Various Generalized Born Models in Different Simulation Programs

Implicit solvent models are widely used because they are advantageous to speed up simulations by drastically decreasing the number of solvent degrees of freedom, which allows one to achieve long simulation time scales for large system sizes. CHARMM-GUI, a web-based platform, has been developed to support the setup of complex multicomponent molecular systems and prepare input files. This study describes an Implicit Solvent Modeler (ISM) in CHARMM-GUI for various generalized Born (GB) implicit solvent simulations in different molecular dynamics programs such as AMBER, CHARMM, GENESIS, NAMD, OpenMM, and Tinker. The GB models available in ISM include GB-HCT, GB-OBC, GB-neck, GBMV, and GBSW with the CHARMM and Amber force fields for protein, DNA, RNA, glycan, and ligand systems. Using the system and input files generated by ISM, implicit solvent simulations of protein, DNA, and RNA systems produce similar results for different simulation packages with the same input information. Protein-ligand systems are also considered to further validate the systems and input files generated by ISM. Simple ligand root-mean-square deviation (RMSD) and molecular mechanics generalized Born surface area (MM/GBSA) calculations show that the performance of implicit simulations is better than docking and can be used for early stage ligand screening. These reasonable results indicate that ISM is a useful and reliable tool to provide various implicit solvent simulation applications.

Osmotic second virial coefficients for hydrophobic interactions as a function of solute size

To gain quantitative insight into how the overall strength of the hydrophobic interaction varies with the molecular size, we calculate osmotic second virial coefficients B for hydrophobic spherical molecules of different diameters σ in water based on molecular simulation with corrections to the finite-size and finite-concentration effects. It is shown that B (<0) changes by two orders of magnitude greater as σ increases twofold and its solute-size dependence is best fit by a power law B ∝ σ^α with the exponent α ≃ 6, which contrasts with the cubic power law that the second virial coefficients of gases obey. It is also found that values of B for the solutes in a nonpolar solvent are positive but they obey the same power law as in water. A thermodynamic identity for B derived earlier [K. Koga, V. Holten, and B. Widom, J. Phys. Chem. B 119, 13391 (2015)] indicates that if B is asymptotically proportional to a power of σ, the exponent α must be equal to or greater than 6.

Recent Developments and Applications of the MMPBSA Method

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.

Ionic Solution: What Goes Right and Wrong with Continuum Solvation Modeling

Solvent-mediated electrostatic interactions were well recognized to be important in the structure and function of molecular systems. Ionic interaction is an important component in electrostatic interactions, especially in highly charged molecules, such as nucleic acids. Here, we focus on the quality of the widely used Poisson-Boltzmann surface area (PBSA) continuum models in modeling ionic interactions by comparing with both explicit solvent simulations and the experiment. In this work, the molality-dependent chemical potentials for sodium chloride (NaCl) electrolyte were first simulated in the SPC/E explicit solvent. Our high-quality simulation agrees well with both the previous study and the experiment. Given the free-energy simulations in SPC/E as the benchmark, we used the same sets of snapshots collected in the SPC/E solvent model for PBSA free-energy calculations in the hope to achieve the maximum consistency between the two solvent models. Our comparative analysis shows that the molality-dependent chemical potentials of NaCl were reproduced well with both linear PB and nonlinear PB methods, although nonlinear PB agrees better with SPC/E and the experiment. Our free-energy simulations also show that the presence of salt increases the hydrophobic effect in a nonlinear fashion, in qualitative agreement with previous theoretical studies of Onsager and Samaras. However, the lack of molality-dependency in the nonelectrostatics continuum models dramatically reduces the overall quality of PBSA methods in modeling salt-dependent energetics. These analyses point to further improvements needed for more robust modeling of solvent-mediated interactions by the continuum solvation frameworks.

Comparison Study of Polar and Nonpolar Contributions to Solvation Free Energy

In this study, we compared the contributions of polar and nonpolar interactions to the solvation free energy of a solute in solvent, which is decomposed into four different terms based on the nature of interactions: (i) electrostatic solvation free energy term counting for the work done to move solute charges from fixed points in some reference environment to their configuration positions in solvent; (ii) solute-solvent van der Waals dispersion interactions; (iii) change on solvent-solvent interactions and solvent entropy due to reorganization of solvent around solute cavity in solvent; and (iv) compensation of electrostatic forces acting on the dielectric surface boundary between solvent and solute. We compared these contributions to each other for a data set of 573 proteins, which were prepared using CHARMM22 and AMBER force fields. In addition, we compared the calculated with experimental hydration free energies for a data set of 642 small molecules, which were prepared using the general AMBER force field. Our results indicated the significance of each term to the total solvation free energy.

Bayesian Model Averaging for Ensemble-Based Estimates of Solvation-Free Energies

This paper applies the Bayesian Model Averaging statistical ensemble technique to estimate small molecule solvation free energies. There is a wide range of methods available for predicting solvation free energies, ranging from empirical statistical models to ab initio quantum mechanical approaches. Each of these methods is based on a set of conceptual assumptions that can affect predictive accuracy and transferability. Using an iterative statistical process, we have selected and combined solvation energy estimates using an ensemble of 17 diverse methods from the fourth Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) blind prediction study to form a single, aggregated solvation energy estimate. Methods that possess minimal or redundant information are pruned from the ensemble and the evaluation process repeats until aggregate predictive performance can no longer be improved. We show that this process results in a final aggregate estimate that outperforms all individual methods by reducing estimate errors by as much as 91% to 1.2 kcal mol^-1 accuracy. This work provides a new approach for accurate solvation free energy prediction and lays the foundation for future work on aggregate models that can balance computational cost with prediction accuracy.

Calculating protein-ligand binding affinities with MMPBSA: Method and error analysis

Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) methods have become widely adopted in estimating protein-ligand binding affinities due to their efficiency and high correlation with experiment. Here different computational alternatives were investigated to assess their impact to the agreement of MMPBSA calculations with experiment. Seven receptor families with both high-quality crystal structures and binding affinities were selected. First the performance of nonpolar solvation models was studied and it was found that the modern approach that separately models hydrophobic and dispersion interactions dramatically reduces RMSD's of computed relative binding affinities. The numerical setup of the Poisson-Boltzmann methods was analyzed next. The data shows that the impact of grid spacing to the quality of MMPBSA calculations is small: the numerical error at the grid spacing of 0.5 Å is already small enough to be negligible. The impact of different atomic radius sets and different molecular surface definitions was further analyzed and weak influences were found on the agreement with experiment. The influence of solute dielectric constant was also analyzed: a higher dielectric constant generally improves the overall agreement with experiment, especially for highly charged binding pockets. The data also showed that the converged simulations caused slight reduction in the agreement with experiment. Finally the direction of estimating absolute binding free energies was briefly explored. Upon correction of the binding-induced rearrangement free energy and the binding entropy lost, the errors in absolute binding affinities were also reduced dramatically when the modern nonpolar solvent model was used, although further developments were apparently necessary to further improve the MMPBSA methods. © 2016 Wiley Periodicals, Inc.

The impact of surface area, volume, curvature, and Lennard-Jones potential to solvation modeling

This article explores the impact of surface area, volume, curvature, and Lennard-Jones (LJ) potential on solvation free energy predictions. Rigidity surfaces are utilized to generate robust analytical expressions for maximum, minimum, mean, and Gaussian curvatures of solvent-solute interfaces, and define a generalized Poisson-Boltzmann (GPB) equation with a smooth dielectric profile. Extensive correlation analysis is performed to examine the linear dependence of surface area, surface enclosed volume, maximum curvature, minimum curvature, mean curvature, and Gaussian curvature for solvation modeling. It is found that surface area and surfaces enclosed volumes are highly correlated to each other's, and poorly correlated to various curvatures for six test sets of molecules. Different curvatures are weakly correlated to each other for six test sets of molecules, but are strongly correlated to each other within each test set of molecules. Based on correlation analysis, we construct twenty six nontrivial nonpolar solvation models. Our numerical results reveal that the LJ potential plays a vital role in nonpolar solvation modeling, especially for molecules involving strong van der Waals interactions. It is found that curvatures are at least as important as surface area or surface enclosed volume in nonpolar solvation modeling. In conjugation with the GPB model, various curvature-based nonpolar solvation models are shown to offer some of the best solvation free energy predictions for a wide range of test sets. For example, root mean square errors from a model constituting surface area, volume, mean curvature, and LJ potential are less than 0.42 kcal/mol for all test sets. © 2016 Wiley Periodicals, Inc.

Examining the assumptions underlying continuum-solvent models

Continuum-solvent models (CSMs) have successfully predicted many quantities, including the solvation-free energies (ΔG) of small molecules, but they have not consistently succeeded at reproducing experimental binding free energies (ΔΔG), especially for protein-protein complexes. Several CSMs break ΔG into the free energy (ΔGvdw) of inserting an uncharged molecule into solution and the free energy (ΔGel) gained from charging. Some further divide ΔGvdw into the free energy (ΔGrep) of inserting a nearly hard cavity into solution and the free energy (ΔGatt) gained from turning on dispersive interactions between the solute and solvent. We show that for 9 protein-protein complexes neither ΔGrep nor ΔGvdw was linear in the solvent-accessible area A, as assumed in many CSMs, and the corresponding components of ΔΔG were not linear in changes in A. We show that linear response theory (LRT) yielded good estimates of ΔGatt and ΔΔGatt, but estimates of ΔΔGatt obtained from either the initial or final configurations of the solvent were not consistent with those from LRT. The LRT estimates of ΔGel differed by more than 100 kcal/mol from the explicit solvent model's (ESM's) predictions, and its estimates of the corresponding component (ΔΔGel) of ΔΔG differed by more than 10 kcal/mol. Finally, the Poisson-Boltzmann equation produced estimates of ΔGel that were correlated with those from the ESM, but its estimates of ΔΔGel were much less so. These findings may help explain why many CSMs have not been consistently successful at predicting ΔΔG for many complexes, including protein-protein complexes.

On the energy components governing molecular recognition in the framework of continuum approaches

Molecular recognition is a process that brings together several biological macromolecules to form a complex and one of the most important characteristics of the process is the binding free energy. Various approaches exist to model the binding free energy, provided the knowledge of the 3D structures of bound and unbound molecules. Among them, continuum approaches are quite appealing due to their computational efficiency while at the same time providing predictions with reasonable accuracy. Here we review recent developments in the field emphasizing on the importance of adopting adequate description of physical processes taking place upon the binding. In particular, we focus on the efforts aiming at capturing some of the atomistic details of the binding phenomena into the continuum framework. When possible, the energy components are reviewed independently of each other. However, it is pointed out that rigorous approaches should consider all energy contributions on the same footage. The two major schemes for utilizing the individual energy components to predict binding affinity are outlined as well.

Effects of geometry and chemistry on hydrophobic solvation

Inserting an uncharged van der Waals (vdw) cavity into water disrupts the distribution of water and creates attractive dispersion interactions between the solvent and solute. This free-energy change is the hydrophobic solvation energy (ΔG(vdw)). Frequently, it is assumed to be linear in the solvent-accessible surface area, with a positive surface tension (γ) that is independent of the properties of the molecule. However, we found that γ for a set of alkanes differed from that for four configurations of decaalanine, and γ = -5 was negative for the decaalanines. These findings conflict with the notion that ΔG(vdw) favors smaller A. We broke ΔG(vdw) into the free energy required to exclude water from the vdw cavity (ΔG(rep)) and the free energy of forming the attractive interactions between the solute and solvent (ΔG(att)) and found that γ < 0 for the decaalanines because -γ(att) > γ(rep) and γ(att) < 0. Additionally, γ(att) and γ(rep) for the alkanes differed from those for the decaalanines, implying that none of ΔG(att), ΔG(rep), and ΔG(vdw) can be computed with a constant surface tension. We also showed that ΔG(att) could not be computed from either the initial or final water distributions, implying that this quantity is more difficult to compute than is sometimes assumed. Finally, we showed that each atom's contribution to γ(rep) depended on multibody interactions with its surrounding atoms, implying that these contributions are not additive. These findings call into question some hydrophobic models.

Solvation free energies of alanine peptides: the effect of flexibility

The electrostatic (ΔGel), van der Waals cavity-formation (ΔGvdw), and total (ΔG) solvation free energies for 10 alanine peptides ranging in length (n) from 1 to 10 monomers were calculated. The free energies were computed both with fixed, extended conformations of the peptides and again for some of the peptides without constraints. The solvation free energies, ΔGel, and components ΔGvdw, and ΔG, were found to be linear in n, with the slopes of the best-fit lines being γel, γvdw, and γ, respectively. Both γel and γ were negative for fixed and flexible peptides, and γvdw was negative for fixed peptides. That γvdw was negative was surprising, as experimental data on alkanes, theoretical models, and MD computations on small molecules and model systems generally suggest that γvdw should be positive. A negative γvdw seemingly contradicts the notion that ΔGvdw drives the initial collapse of the protein when it folds by favoring conformations with small surface areas. When we computed ΔGvdw for the flexible peptides, thereby allowing the peptides to assume natural ensembles of more compact conformations, γvdw was positive. Because most proteins do not assume extended conformations, a ΔGvdw that increases with increasing surface area may be typical for globular proteins. An alternative hypothesis is that the collapse is driven by intramolecular interactions. We find few intramolecular H-bonds but show that the intramolecular van der Waals interaction energy is more favorable for the flexible than for the extended peptides, seemingly favoring this hypothesis. The large fluctuations in the vdw energy may make attributing the collapse of the peptide to this intramolecular energy difficult.

Specific and non-specific protein association in solution: computation of solvent effects and prediction of first-encounter modes for efficient configurational bias Monte Carlo simulations

Weak and ultraweak protein-protein association play a role in molecular recognition and can drive spontaneous self-assembly and aggregation. Such interactions are difficult to detect experimentally, and are a challenge to the force field and sampling technique. A method is proposed to identify low-population protein-protein binding modes in aqueous solution. The method is designed to identify preferential first-encounter complexes from which the final complex(es) at equilibrium evolve. A continuum model is used to represent the effects of the solvent, which accounts for short- and long-range effects of water exclusion and for liquid-structure forces at protein/liquid interfaces. These effects control the behavior of proteins in close proximity and are optimized on the basis of binding enthalpy data and simulations. An algorithm is described to construct a biasing function for self-adaptive configurational-bias Monte Carlo of a set of interacting proteins. The function allows mixing large and local changes in the spatial distribution of proteins, thereby enhancing sampling of relevant microstates. The method is applied to three binary systems. Generalization to multiprotein complexes is discussed.

Confinement induced conformational changes in n-alkanes sequestered within a narrow carbon nanotube

While alkanes in solution exhibit predominantly extended conformations, nanoscale confinement of these chains within protein binding sites and synthetic receptors can significantly alter the conformer distribution. As a simple model for the effect of confinement on the conformation, we report molecular simulations of n-alkanes absorbed from a bulk solvent into narrow carbon nanotubes. We observe that confinement of butane, hexane, and tetracosane induces a trans to gauche conformational redistribution. Moreover, confined hexane and tetracosane exhibit cooperative interactions between neighboring dihedral angles, which promote a helical gauche conformation for the portions of the chain within the nanotube. Hexane absorbed into the nanotube from water or benzene exhibits essentially the same conformation regardless of the bulk solvent. The PMF between the nanotube and hexane along the central nanotube axis finds that nanotube absorption is favorable from aqueous solution but neutral from benzene. The interaction between hexane and the nanotube in water is dominated by the direct interaction between the alkane and the nanotube and weakly opposed by indirect water-mediated forces. In benzene, however, the direct alkane/nanotube interaction is effectively balanced by the indirect benzene-mediated interaction. Our simulations in water stand in difference to standard interpretations of the hydrophobic effect, which posit that the attraction between non-polar species in water is driven by their mutual insolubility.

Putting the squeeze on cavities in liquids: Quantifying pressure effects on solvation using simulations and scaled-particle theory

Extensive molecular simulations of the Lennard-Jones fluid are performed to examine the response of the excess chemical potential of cavitylike solutes to applied pressure. Solutes as large as ten times the solvent diameter are considered. The simulations are analyzed using the revised scaled-particle theory developed by Ashbaugh and Pratt to evaluate the thermodynamics of cavity solvation and curvature dependent interfacial properties well into the compressed liquid portion of the solvent phase diagram. The revised theory provides a quantitatively accurate description of the solvent-solute contact correlation function for all solutes and state points considered. The main structural effect of increasing pressure is to push the solvent molecules up against the solute surfaces, counteracting the dewetting that is observed at lower pressures along the solvent saturation curve. Decomposing the excess chemical potential of cavities into volume and surface-area contributions shows that pressure differentially affects the interfacial free energies of molecular versus macroscopic solutes. The interfacial free energy of surfaces of molecular dimension monotonically decreases with applied pressure, while that of surfaces larger than a small cluster of solvent molecules exhibit a maximum with increasing pressure, which may play a role in pressure-induced disaggregation of molecular assemblies. Moreover, since the pressure dependence of the interfacial free energy is thermodynamically linked to the excess adsorption of solvent on the solute surface, the former is potentially a measurable macroscopic indicator of microscopic wetting∕dewetting phenomena, implicated in hydrophobic interactions between macroscopic hydrophobic particles. Finally, some inferences about pressure-dependent solvation processes in water are made by using the revised theory to analyze previously published simulation data.

DFT and MP2 investigations of L-proline and its hydrated complexes

A theoretical study of L-proline-nH(2)O (n = 1-3) has been performed using the hybrid DFT-B3LYP and MP2 methods together with the 6-311++G(d,p) basis set. The results show that the P2 conformer is energetically favorable when forming a hydrated structure, and the hydration of the carboxyl group leads to the greatest stability. For hydrated complexes, the adiabatic and vertical singlet-triplet excitation energies tend to decrease with the addition of water molecules. The hydration energy indicates that in the hydrated complexes the order of stability is: binding site 2 > binding site 1 > binding site 3, and binding site 12 > binding site 23 > binding site 13. As water molecules are added, the stabilities of these hydrated structures gradually increase. In addition, an infrared frequency analysis indicated that there are some differences in the low-frequency range, which are mainly dominated by the O-H stretching or bending vibrations of different water molecules. All of these results should aid our understanding of molecular behavior and provide reference data for further studies of biological systems.

Direct Measurement of the Kinetics and Thermodynamics of Association of Hydrophobic Molecules from Molecular Dynamics Simulations

A detailed study of the kinetics and thermodynamics of associations of model hydrophobic molecules is likely to be valuable for understanding the fundamental driving forces for processes such as protein folding and protein-protein association. To this end, we present results from a series of 500 ns long molecular dynamics (MD) simulations examining associations of 13 types of different alkane pairs in explicit water. In addition to providing accurate measurements of the association thermodynamics, the unbiased nature of the configurational sampling in the MD simulations allows the association and dissociation kinetics to be directly quantified. We show that by choosing a suitable reaction coordinate, the computed free energies of all of the alkane-alkane complexes can be linearly related to their buried molecular surface areas, that their dissociation kinetics can be reliably estimated from the height of the barrier on the computed free energy surfaces, and that their association kinetics are effectively diffusion-limited.

Stochastic model of self-assembly of cell-laden hydrogels

Recent progress in bottom-up tissue engineering has demonstrated that three-dimensional tissue constructs with predefined architectures may be obtained by assembling shape-controlled hydrogels in multiphase reactor systems. Driven by the hydrophobic force between gel unit and liquid media, highly ordered hydrogel clusters can be formed. Many complex factors occurring at microscale (i.e., gel unit collisions, hydrophobic forces, and gel unit movement) are involved in the self-assembly process. In this paper a two-dimensional off-lattice Monte Carlo model with Lennard-Jones-type potential describing unit-unit interactions is introduced for studying this process. Simulations are shown to agree well with the experimental results for hydrogel assembly in mineral oil. The simulation method is demonstrated for rectangular hydrogel units of different aspect ratios as well as extended to the case of more complex hydrogel unit geometries.

The AGBNP2 Implicit Solvation Model

The AGBNP2 implicit solvent model, an evolution of the Analytical Generalized Born plus Non-Polar (AGBNP) model we have previously reported, is presented with the aim of modeling hydration effects beyond those described by conventional continuum dielectric representations. A new empirical hydration free energy component based on a procedure to locate and score hydration sites on the solute surface is introduced to model first solvation shell effects, such as hydrogen bonding, which are poorly described by continuum dielectric models. This new component is added to the Generalized Born and non-polar AGBNP terms. Also newly introduced is an analytical Solvent Excluded Volume (SEV) model which improves the solute volume description by reducing the effect of spurious high-dielectric interstitial spaces present in conventional van der Waals representations. The AGBNP2 model is parametrized and tested with respect to experimental hydration free energies of small molecules and the results of explicit solvent simulations. Modeling the granularity of water is one of the main design principles employed for the the first shell solvation function and the SEV model, by requiring that water locations have a minimum available volume based on the size of a water molecule. It is shown that the new volumetric model produces Born radii and surface areas in good agreement with accurate numerical evaluations of these quantities. The results of molecular dynamics simulations of a series of mini-proteins show that the new model produces conformational ensembles in substantially better agreement with reference explicit solvent ensembles than the original AGBNP model with respect to both structural and energetics measures.

Predictions of hydration free energies from all-atom molecular dynamics simulations

Here, we computed the aqueous solvation (hydration) free energies of 52 small drug-like molecules using an all-atom force field in explicit water. This differs from previous studies in that (1) this was a blind test (in an event called SAMPL sponsored by OpenEye Software) and (2) the test compounds were considerably more challenging than have been used in the past in typical solvation tests of all-atom models. Overall, we found good correlations with experimental values which were subsequently made available, but the variances are large compared to those in previous tests. We tested several different charge models and found that several standard charge models performed relatively well. We found that hypervalent sulfur and phosphorus compounds are not well handled using current force field parameters and suggest several other possible systematic errors. Overall, blind tests like these appear to provide significant opportunities for improving force fields and solvent models.

Small molecule hydration free energies in explicit solvent: An extensive test of fixed-charge atomistic simulations

Using molecular dynamics free energy simulations with TIP3P explicit solvent, we compute the hydration free energies of 504 neutral small organic molecules and compare them to experiments. We find, first, good general agreement between the simulations and the experiments, with an RMS error of 1.24 kcal/mol over the whole set (i.e., about 2 kT) and a correlation coefficient of 0.89. Second, we use an automated procedure to identify systematic errors for some classes of compounds, and suggest some improvements to the force field. We find that alkyne hydration free energies are particularly poorly predicted due to problems with a Lennard-Jones well depth, and find that an alternate choice for this well depth largely rectifies the situation. Third, we study the non-polar component of hydration free energies - that is, the part that is not due to electrostatics. While we find that repulsive and attractive components of the non-polar part both scale roughly with surface area (or volume) of the solute, the total non-polar free energy does not scale with the solute surface area or volume, because it is a small difference between large components and is dominated by the deviations from the trend. While the methods used here are not new, this is a more extensive test than previous explicit solvent studies, and the size of the test set allows identification of systematic problems with force field parameters for particular classes of compounds. We believe that the computed free energies and components will be valuable to others in future development of force fields and solvation models.

Implicit modeling of nonpolar solvation for simulating protein folding and conformational transitions

Accurate description of the solvent environment is critical in computer simulations of protein structure and dynamics. An implicit treatment of solvent aims to capture the mean influence of water molecules on the solute via direct estimation of the solvation free energy. It has emerged as a powerful alternative to explicit solvent, and provides a favorable compromise between computational cost and level of detail. We review the current theory and techniques for implicit modeling of nonpolar solvation in the context of simulating protein folding and conformational transitions, and discuss the main directions for further development. It is demonstrated that the current surface area based nonpolar models have severe limitations, including insufficient description of the conformational dependence of solvation, over-estimation of the strength of pair-wise nonpolar interactions, and incorrect prediction of anti-cooperativity for three-body hydrophobic associations. We argue that, to improve beyond current level of accuracy of implicit solvent models, two important aspects of nonpolar solvation need to be incorporated, namely, the length-scale dependence of hydrophobic association and solvent screening of solute-solute dispersion interactions. We recognize that substantial challenges exist in constructing a sufficiently balanced, yet reasonably efficient, implicit solvent protein force field. Nonetheless, most of the fundamental problems are understood, and exciting progress has been made over the last few years. We believe that continual work along the frontiers outlined will greatly improve one's ability to study protein folding and large conformational transitions at atomistic detail.

Implicit nonpolar solvent models

We have systematically analyzed a new nonpolar solvent model that separates nonpolar solvation free energy into repulsive and attractive components. Our analysis shows that either molecular surfaces or volumes can be used to correlate with repulsive free energies of tested molecules in explicit solvent with correlation coefficients higher than 0.99. In addition, the attractive free energies in explicit solvent can also be reproduced with the new model with a correlation coefficient higher than 0.999. Given each component optimized, the new nonpolar solvent model is found to reproduce monomer nonpolar solvation free energies in explicit solvent very well. However, the overall accuracy of the nonpolar solvation free energies is lower than that of each component. In the more challenging dimer test cases, the agreement of the new model with explicit solvent is less impressive. Nevertheless, it is found that the new model works reasonably well for reproducing the relative nonpolar free energy landscapes near the global minimum of the dimer complexes.

On the salt-induced stabilization of pair and many-body hydrophobic interactions

Salting-out of hydrophobic solutes in aqueous salt solutions and their relevance to salt effects on biophysical phenomena are now well appreciated. Although salt effects on hydrophobic transfer have been well studied, to our knowledge, no quantitative molecular simulation study of salt-induced strengthening of hydrophobic interactions has yet been reported. Here we present quantitative characterization of salt-induced strengthening of hydrophobic interactions at the molecular and nanoscopic length scales through molecular dynamics simulations. Specifically, we quantify the effect of NaCl on the potential of mean force between molecular hydrophobic solutes (methanes) and on conformational equilibria of a 25-mer hydrophobic polymer that efficiently samples ensembles of compact and extended states in water. In both cases, we observe relative stabilization of compact conformations that is accompanied by a clear depletion of salt density (preferential exclusion) and a slight enhancement of water density (preferential hydration) in the solute vicinity. We show that the structural details of salt exclusion can be related to the salt-induced free energy changes using preferential interaction coefficients. We also test the applicability of surface-area-based models to describe the salt-induced free energy changes. These models provide a useful empirical description that can be used to predict the effects of salt on conformational equilibria of hydrophobic solutes. However, we find that the effective increase in the surface tension of the solute-aqueous solution interface depends on the type and concentration of salt as well as the length-scale (i.e., molecular vs nanoscopic) of the conformational change. These calculations underscore the utility of simulation studies to connect quantitatively structural details at the molecular level (described by preferential hydration/exclusion) to macroscopic solvation thermodynamics. The hydrophobic polymer also provides a useful model for studies of effect of thermodynamic variables (P, T, salt/additives) on many-body hydrophobic interactions at nanometer length scales.

Molecular Solvation in Water−Methanol and Water−Sorbitol Mixtures: The Roles of Preferential Hydration, Hydrophobicity, and the Equation of State

Molecular dynamics simulations of aqueous mixtures of methanol and sorbitol were performed over a wide range of binary composition, density (pressure), and temperature to study the equation of state and solvation of small apolar solutes. Experimentally, methanol is a canonical solubilizing agent for apolar solutes and a protein denaturant in mixed-aqueous solvents; sorbitol represents a canonical "salting-out" or protein-stabilizing cosolvent. The results reported here show increasing sorbitol concentration under isothermal, isobaric conditions results in monotonic increases in apolar solute excess chemical potential (mu2ex) over the range of experimentally relevant temperatures. For methanol at elevated temperatures, increasing cosolvent composition results in monotonically decreasing mu2ex. However, at lower temperatures mu2ex exhibits a maximum versus cosolvent concentration, as seen experimentally for Ar in ethanol-water solutions. Both density anomalies and hydrophobic effects--characterized by temperatures of density maxima and apolar solute solubility minima, respectively--are suppressed upon addition of either sorbitol or methanol at all temperatures and compositions simulated here. Thus, the contrasting effects of sorbitol and methanol on solute chemical potential cannot be explained by qualitative differences in their ability to enhance or suppress hydrophobic effects. Rather, we find mu2ex values across a broad range of temperatures and cosolvent composition can be quantitatively explained in terms of isobaric changes in solvent density--i.e., the equation of state--along with the corresponding packing fraction of the solvent. Analysis in terms of truncated preferential interaction parameters highlights that care must be taken in interpreting cosolvent effects on solvation in terms of local preferential hydration.

Excess densities and equimolar surfaces for spherical cavities in water

For hard spheres with a radius up to 10 A in TIP4P water under ambient conditions, the author studies how the excess number of molecules at the accessible surface depends on the radius of the cavity. Simulation results derived from excess volumes are discussed in terms of radial distribution functions (rdfs), which compare well with extended simple point charge and theoretical rdfs from the literature. The excess number of molecules at the accessible surface inserted in the expression which refers to an arbitrary dividing surface enables one to find the position of the equimolar surface. The surface tension corresponding to this dividing surface was obtained from values of the free energy of cavity formation. For radii in the range of the simulation data, its behavior with curvature is quite different from that usually shown in the literature. A model, which describes how the excess number of molecules at the accessible surface changes with the radius, is discussed in the large length limit by examining consistent rdfs described by a simple analytical form. The inclusion in the model of a logarithmic term has also been considered. Comparison with theoretical results from the literature shows a good agreement for a cavity with a radius of 20 A. For a radius of 100 A and beyond, the model predicts instead sharper density profiles. Such differences have a poor effect on the surface tension at the equimolar surface.

Assessing the Protonation State of Drug Molecules: The Case of Aztreonam

Herein we examine the viability of physicochemical approaches based on standard computational chemistry tools to characterize the structure and energetics of flexible drug molecules with various titratable sites. We focus on the case of the monobactam antibiotic aztreonam, whose structure and physicochemical properties have been ascribed to several tautomeric forms, although it is still unclear which protonation states are responsible for its biological activity. First, we experimentally determined the pKa values for aztreonam over the pH range 0.8-7.0 using both 1H NMR and 13C NMR spectroscopy. Second, we carried out quantum chemical calculations on snapshots extracted from classical molecular dynamics simulations. Various levels of approximation were used in the energy calculations: ONIOM(HF/3-21G*:AMBER) for geometry relaxation, B3LYP/6-31+G** for electronic and electrostatic solvation energies, and molecular mechanics for attractive dispersion energy. The value of the free energy of solvation of a proton was treated as a parameter and chosen to give the best match between calculated and experimental pKa values for small molecules. Overall, this computational scheme can give satisfactory results in the pKa calculations for drug molecules.

Calculation of Solvation Free Energy from Quantum Mechanical Charge Density and Continuum Dielectric Theory

We have combined ultrasoft pseudopotential density functional theory utilizing plane wave basis with a Poisson-Boltzmann/solvent-accessible surface area (PB/SA) model to calculate the solvation free energy of small neutral organic compounds in water. The solute charge density obtained from density functional theory was directly used in solving the Poisson-Boltzmann equation to obtain the reaction field. The polarized electronic wave function of the solute in the solvent was solved by including the reaction field in the density functional Hamiltonian. The quantum mechanical and Poisson-Boltzmann equations were solved self-consistently until the charge density and reaction field converged. Using the solute charge density directly instead of a point-charge representation permitted asymmetric distortion and spreading out of the electron cloud. Because the electron density could leave the van der Waals surface to penetrate into the high-dielectric solvent, the reaction field generated by this density was generally smaller than that obtained by using the point-charge representation. In applying this model to calculate the solvation free energy of 31 small neutral organic molecules spanning a range of 25 kcal/mol, we obtained a root-mean-square error of only 1.3 kcal/mol if we allowed one adjustable parameter to shift the calculated solvation free energy.

Computation of hydration free energies of organic solutes with an implicit water model

A new approach for computing hydration free energies DeltaG(solv) of organic solutes is formulated and parameterized. The method combines a conventional PCM (polarizable continuum model) computation for the electrostatic component DeltaG(el) of DeltaG(solv) and a specially detailed algorithm for treating the complementary nonelectrostatic contributions (DeltaG(nel)). The novel features include the following: (a) two different cavities are used for treating DeltaG(el) and DeltaG(nel). For the latter case the cavity is larger and based on thermal atomic radii (i.e., slightly reduced van der Waals radii). (b) The cavitation component of DeltaG(nel) is taken to be proportional to the volume of the large cavity. (c) In the treatment of van der Waals interactions, all solute atoms are counted explicitly. The corresponding interaction energies are computed as integrals over the surface of the larger cavity; they are based on Lennard Jones (LJ) type potentials for individual solute atoms. The weighting coefficients of these LJ terms are considered as fitting parameters. Testing this method on a collection of 278 uncharged organic solutes gave satisfactory results. The average error (RMSD) between calculated and experimental free energy values varies between 0.15 and 0.5 kcal/mol for different classes of solutes. The larger deviations found for the case of oxygen compounds are probably due to a poor approximation of H-bonding in terms of LJ potentials. For the seven compounds with poorest fit to experiment, the error exceeds 1.5 kcal/mol; these outlier points were not included in the parameterization procedure. Several possible origins of these errors are discussed.

Modeling the Cavitation Free Energy

A new expression to compute the cavitation free energy has been derived by integrating a new model to fit its derivative with respect to the cavity radius. The derivatives were obtained from Monte Carlo simulations data of the contact values of distribution functions for hard-sphere solutes in TIP4P water at 298 K and 1 atm. The new expression, formulated in the framework of the thermodynamics of surfaces and unlike the classical simple models, gives good results also for very small cavities with a radius of approximately 1 A. The contribution to the free energy of a term, which depends on the excess number of molecules at the dividing surface, has been taken into account and discussed for the assumed dependence on r of the surface tension. The asymptotic behavior of the derivative has thus been considered, and a function t(r), which is 0 at r = 0 and 1 at infinity, has been introduced to describe the transition from small to large length regimes. The value of the surface tension obtained by fitting is in very good agreement with that obtained from a simulation of the liquid/vapor interface by using the TIP4P model.

Integrated Modeling Program, Applied Chemical Theory (IMPACT)

We provide an overview of the IMPACT molecular mechanics program with an emphasis on recent developments and a description of its current functionality. With respect to core molecular mechanics technologies we include a status report for the fixed charge and polarizable force fields that can be used with the program and illustrate how the force fields, when used together with new atom typing and parameter assignment modules, have greatly expanded the coverage of organic compounds and medicinally relevant ligands. As we discuss in this review, explicit solvent simulations have been used to guide our design of implicit solvent models based on the generalized Born framework and a novel nonpolar estimator that have recently been incorporated into the program. With IMPACT it is possible to use several different advanced conformational sampling algorithms based on combining features of molecular dynamics and Monte Carlo simulations. The program includes two specialized molecular mechanics modules: Glide, a high-throughput docking program, and QSite, a mixed quantum mechanics/molecular mechanics module. These modules employ the IMPACT infrastructure as a starting point for the construction of the protein model and assignment of molecular mechanics parameters, but have then been developed to meet specialized objectives with respect to sampling and the energy function.

The non-polar solvent potential of mean force for the dimerization of alanine dipeptide: the role of solute-solvent van der Waals interactions

The non-polar component of the potential of mean force of dimerization of alanine dipeptide has been calculated in explicit solvent by free energy perturbation. We observe that the calculated PMF is inconsistent with a non-polar hydration free energy model based solely on the solute surface area. The non-linear behavior of the solute-solvent van der Waals energy is primarily responsible for the non-linear dependence of the potential of mean force with respect to the surface area. The calculated potential of mean force is reproduced by an implicit solvent model based on a solvent continuum model for the solute-solvent van der Waals interaction energy and the surface area for the work of forming the solute cavity.

Interfaces and the driving force of hydrophobic assembly

The hydrophobic effect--the tendency for oil and water to segregate--is important in diverse phenomena, from the cleaning of laundry, to the creation of micro-emulsions to make new materials, to the assembly of proteins into functional complexes. This effect is multifaceted depending on whether hydrophobic molecules are individually hydrated or driven to assemble into larger structures. Despite the basic principles underlying the hydrophobic effect being qualitatively well understood, only recently have theoretical developments begun to explain and quantify many features of this ubiquitous phenomenon.

Detailed considerations for a balanced and broadly applicable force field: A study of substituted benzenes modeled with OPLS-AA

Modern classical force fields have been traditionally parameterized by attempting to maximize agreement to any number of experimental and/or quantum mechanical target properties. As these force fields are pushed towards obtaining quantitative estimates of often subtle energetic differences, stringent and consistent parameterization criteria, particularly in regard to charge distributions, are required to ensure that systematic errors cancel, that parameters are transferable between molecules, and that performance does not significantly deteriorate when using more approximate methods, such as with continuum solvent models. Relative free energies of hydration are presented here for 40 mono- and disubstituted benzenes modeled with the OPLS-AA force field; heats of vaporization and pure liquid densities at standard conditions are presented when experimental data is available. Overall agreement between OPLS-AA and experiment is remarkable (average error = 0.5 kcal/mol for DeltaDeltaG(hydration), 1.0 kcal/mol for DeltaH(vap) (0), 0.02 g/mL for densities), yet several functional groups are identified as having consistent and correctable errors (alkyl-, nitro-, and thiobenzenes). Relative free energies of hydration obtained with rigorous free energy perturbations using explicit solvent are also compared with energies from minimizations using a generalized Born model (GB). There is high correlation between these estimates (R = 0.99), and as demonstrated here, reparameterization of the aforementioned groups can be guided with rapid GB calculations.

Assessing scoring functions for protein-ligand interactions

An assessment of nine scoring functions commonly applied in docking using a set of 189 protein-ligand complexes is presented. The scoring functions include the CHARMm potential, the scoring function DrugScore, the scoring function used in AutoDock, the three scoring functions implemented in DOCK, as well as three scoring functions implemented in the CScore module in SYBYL (PMF, Gold, ChemScore). We evaluated the abilities of these scoring functions to recognize near-native configurations among a set of decoys and to rank binding affinities. Binding site decoys were generated by molecular dynamics with restraints. To investigate whether the scoring functions can also be applied for binding site detection, decoys on the protein surface were generated. The influence of the assignment of protonation states was probed by either assigning "standard" protonation states to binding site residues or adjusting protonation states according to experimental evidence. The role of solvation models in conjunction with CHARMm was explored in detail. These include a distance-dependent dielectric function, a generalized Born model, and the Poisson equation. We evaluated the effect of using a rigid receptor on the outcome of docking by generating all-pairs decoys ("cross-decoys") for six trypsin and seven HIV-1 protease complexes. The scoring functions perform well to discriminate near-native from misdocked conformations, with CHARMm, DOCK-energy, DrugScore, ChemScore, and AutoDock yielding recognition rates of around 80%. Significant degradation in performance is observed in going from decoy to cross-decoy recognition for CHARMm in the case of HIV-1 protease, whereas DrugScore and ChemScore, as well as CHARMm in the case of trypsin, show only small deterioration. In contrast, the prediction of binding affinities remains problematic for all of the scoring functions. ChemScore gives the highest correlation value with R(2) = 0.51 for the set of 189 complexes and R(2) = 0.43 for the set of 116 complexes that does not contain any of the complexes used to calibrate this scoring function. Neither a more accurate treatment of solvation nor a more sophisticated charge model for zinc improves the quality of the results. Improved modeling of the protonation states, however, leads to a better prediction of binding affinities in the case of the generalized Born and the Poisson continuum models used in conjunction with the CHARMm force field.

AGBNP: an analytic implicit solvent model suitable for molecular dynamics simulations and high-resolution modeling

We have developed an implicit solvent effective potential (AGBNP) that is suitable for molecular dynamics simulations and high-resolution modeling. It is based on a novel implementation of the pairwise descreening Generalized Born model for the electrostatic component and a new nonpolar hydration free energy estimator. The nonpolar term consists of an estimator for the solute-solvent van der Waals dispersion energy designed to mimic the continuum solvent solute-solvent van der Waals interaction energy, in addition to a surface area term corresponding to the work of cavity formation. AGBNP makes use of a new parameter-free algorithm to calculate the scaling coefficients used in the pairwise descreening scheme to take into account atomic overlaps. The same algorithm is also used to calculate atomic surface areas. We show that excellent agreement is achieved for the GB self-energies and surface areas in comparison to accurate, but much more expensive, numerical evaluations. The parameter-free approach used in AGBNP and the sensitivity of the AGBNP model with respect to large and small conformational changes makes the model suitable for high-resolution modeling of protein loops and receptor sites as well as high-resolution prediction of the structure and thermodynamics of protein-ligand complexes. We present illustrative results for these kinds of benchmarks. The model is fully analytical with first derivatives and is computationally efficient. It has been incorporated into the IMPACT molecular simulation program.