Effect of Solvent Discreteness on Solvation

The electrostatic response of water to neutral polar solutes: implications for continuum solvent modeling

Continuum solvation models are widely used to estimate the hydration free energies of small molecules and proteins, in applications ranging from drug design to protein engineering, and most such models are based on the approximation of a linear dielectric response by the solvent. We used explicit-water molecular dynamics simulations with the TIP3P water model to probe this linear response approximation in the case of neutral polar molecules, using miniature cucurbituril and cyclodextrin receptors and protein side-chain analogs as model systems. We observe supralinear electrostatic solvent responses, and this nonlinearity is found to result primarily from waters' being drawn closer and closer to the solutes with increased solute-solvent electrostatic interactions; i.e., from solute electrostriction. Dielectric saturation and changes in the water-water hydrogen bonding network, on the other hand, play little role. Thus, accounting for solute electrostriction may be a productive approach to improving the accuracy of continuum solvation models.

Biomolecular electrostatics and solvation: a computational perspective

An understanding of molecular interactions is essential for insight into biological systems at the molecular scale. Among the various components of molecular interactions, electrostatics are of special importance because of their long-range nature and their influence on polar or charged molecules, including water, aqueous ions, proteins, nucleic acids, carbohydrates, and membrane lipids. In particular, robust models of electrostatic interactions are essential for understanding the solvation properties of biomolecules and the effects of solvation upon biomolecular folding, binding, enzyme catalysis, and dynamics. Electrostatics, therefore, are of central importance to understanding biomolecular structure and modeling interactions within and among biological molecules. This review discusses the solvation of biomolecules with a computational biophysics view toward describing the phenomenon. While our main focus lies on the computational aspect of the models, we provide an overview of the basic elements of biomolecular solvation (e.g. solvent structure, polarization, ion binding, and non-polar behavior) in order to provide a background to understand the different types of solvation models.

Self-consistent treatment of the local dielectric permittivity and electrostatic potential in solution for polarizable macromolecular force fields

A self-consistent method is presented for the calculation of the local dielectric permittivity and electrostatic potential generated by a solute of arbitrary shape and charge distribution in a polar and polarizable liquid. The structure and dynamics behavior of the liquid at the solute/liquid interface determine the spatial variations of the density and the dielectric response. Emphasis here is on the treatment of the interface. The method is an extension of conventional methods used in continuum protein electrostatics, and can be used to estimate changes in the static dielectric response of the liquid as it adapts to charge redistribution within the solute. This is most relevant in the context of polarizable force fields, during electron structure optimization in quantum chemical calculations, or upon charge transfer. The method is computationally efficient and well suited for code parallelization, and can be used for on-the-fly calculations of the local permittivity in dynamics simulations of systems with large and heterogeneous charge distributions, such as proteins, nucleic acids, and polyelectrolytes. Numerical calculation of the system free energy is discussed for the general case of a liquid with field-dependent dielectric response.

Physical Modeling of Aqueous Solvation

We consider the free energies of solvating molecules in water. Computational modeling usually involves either detailed explicit-solvent simulations, or faster computations, which are based on implicit continuum approximations or additivity assumptions. These simpler approaches often miss microscopic physical details and non-additivities present in experimental data. We review explicit-solvent modeling that identifies the physical bases for the errors in the simpler approaches. One problem is that water molecules that are shared between two substituent groups often behave differently than waters around each substituent individually. One manifestation of non-additivities is that solvation free energies in water can depend not only on surface area or volume, but on other properties, such as the surface curvature. We also describe a new computational approach, called Semi-Explicit Assembly, that aims to repair these flaws and capture more of the physics of explicit water models, but with computational efficiencies approaching those of implicit-solvent models.

Modeling aqueous solvation with semi-explicit assembly

We describe a computational solvation model called semi-explicit assembly (SEA). SEA water captures much of the physics of explicit-solvent models but with computational speeds approaching those of implicit-solvent models. We use an explicit-water model to precompute properties of water solvation shells around simple spheres, then assemble a solute's solvation shell by combining the shells of these spheres. SEA improves upon implicit-solvent models of solvation free energies by accounting for local solute curvature, accounting for near-neighbor nonadditivities, and treating water's dipole as being asymmetrical with respect to positive or negative solute charges. SEA does not involve parameter fitting, because parameters come from the given underlying explicit-solvation model. SEA is about as accurate as explicit simulations as shown by comparisons against four different homologous alkyl series, a set of 504 varied solutes, solutes taken retrospectively from two solvation-prediction events, and a hypothetical polar-solute series, and SEA is about 100-fold faster than Poisson-Boltzmann calculations.

Toward accurate microscopic calculation of solvation entropies: extending the restraint release approach to studies of solvation effects

The evaluation of the solvation entropies is a major conceptual and practical challenge. On the one hand, it is interesting to quantify the factors that are responsible for the solvation entropies in solutions, whereas on the other, it is essential to be able to assess the contributions of the solvation entropies to the binding free energies and related properties. In fact, the solvation entropies are neglected in almost all of the studies of the binding entropies. The main problem is that widely used approaches, such as the quasiharmonic (QH) approximation, do not provide reliable results particularly in cases of shallow potential and multidimensional surfaces while brute force evaluations of the entropic effects by simulating temperature dependence of the free energy converges very slowly. This paper addresses the above issue by starting with an analysis of the factors that are responsible for the negative solvation entropy of ions, showing that it is not due to the change in the solvent vibration modes or to the solvent force constant but to the changes in the solvent configurational space upon change in the solute charges. We begin by clarifying that when one deals with aqueous solutions, it is easy to evaluate the corresponding entropic effect by the Langevin dipole (LD) treatment. However, in this work we are interested in developing a general microscopic tool that can be used to study similar effects in the proteins. To this end, we explore the ability of our restraint release (RR) approach to evaluate the solvation entropy. We start this analysis by reviewing the foundation of this approach and in particular, the requirements of minimizing the enthalpy contribution to the RR free energy. We then establish that our approach is not a specialized harmonic treatment but a rather powerful general approach. Moving to the main topic of this work, we demonstrate that the RR approach provides quantitative results for the solvation entropies of monovalent and divalent ions and effectively captures the physics of these entropic effects. The success of the current approach indicates that it should be applicable to the studies of the solvation entropies in the proteins and also, in examining hydrophobic effects. Thus, we believe that the RR approach provides a powerful tool for evaluating the corresponding contributions to the binding entropies and, eventually, to the binding free energies. This holds promise for extending the information theory modeling to proteins and protein-ligand complexes in aqueous solutions and consequently, facilitating computer-aided drug design.

"Tetrahedrality" and the relationship between collective structure and radial distribution functions in liquid water

Molecular dynamics simulations of pure liquid water under ambient conditions using four common empirical water models have been analyzed to determine how well the oxygen-oxygen radial distribution function, g(OO)(r), used as the sole criterion of congruence with experiment, captures variations in the actual anisotropic collective structuring for these models. The largest systematic deviations from tetrahedrality were found to be due to deformations of the angle between the two closet hydrogen bond donor neighbors, but for intrinsic geometric reasons, these were found to contribute less to g(OO)(r) than deformations of the angles between one hydrogen bond donor neighbor and one hydrogen bond acceptor neighbor. Relying exclusively on a qualitative characterization of the second peak in g(OO)(r) seems to overemphasize the differences between the structuring in some of these models.

Modeling electrostatic effects in proteins

Electrostatic energies provide what is perhaps the most effective tool for structure-function correlation of biological molecules. This review considers the current state of simulations of electrostatic energies in macromolecules as well as the early developments of this field. We focus on the relationship between microscopic and macroscopic models, considering the convergence problems of the microscopic models and the fact that the dielectric 'constants' in semimacroscopic models depend on the definition and the specific treatment. The advances and the challenges in the field are illustrated considering a wide range of functional properties including pK(a)'s, redox potentials, ion and proton channels, enzyme catalysis, ligand binding and protein stability. We conclude by pointing out that, despite the current problems and the significant misunderstandings in the field, there is an overall progress that should lead eventually to quantitative descriptions of electrostatic effects in proteins and thus to quantitative descriptions of the function of proteins.

Long dynamics simulations of proteins using atomistic force fields and a continuum representation of solvent effects: calculation of structural and dynamic properties

Long dynamics simulations were carried out on the B1 immunoglobulin-binding domain of streptococcal protein G (ProtG) and bovine pancreatic trypsin inhibitor (BPTI) using atomistic descriptions of the proteins and a continuum representation of solvent effects. To mimic frictional and random collision effects, Langevin dynamics (LD) were used. The main goal of the calculations was to explore the stability of tens-of-nanosecond trajectories as generated by this molecular mechanics approximation and to analyze in detail structural and dynamical properties. Conformational fluctuations, order parameters, cross correlation matrices, residue solvent accessibilities, pKa values of titratable groups, and hydrogen-bonding (HB) patterns were calculated from all of the trajectories and compared with available experimental data. The simulations comprised over 40 ns per trajectory for ProtG and over 30 ns per trajectory for BPTI. For comparison, explicit water molecular dynamics simulations (EW/MD) of 3 ns and 4 ns, respectively, were also carried out. Two continuum simulations were performed on each protein using the CHARMM program, one with the all-atom PAR22 representation of the protein force field (here referred to as PAR22/LD simulations) and the other with the modifications introduced by the recently developed CMAP potential (CMAP/LD simulations). The explicit solvent simulations were performed with PAR22 only. Solvent effects are described by a continuum model based on screened Coulomb potentials (SCP) reported earlier, i.e., the SCP-based implicit solvent model (SCP-ISM). For ProtG, both the PAR22/LD and the CMAP/LD 40-ns trajectories were stable, yielding C(alpha) root mean square deviations (RMSD) of about 1.0 and 0.8 A respectively along the entire simulation time, compared to 0.8 A for the EW/MD simulation. For BPTI, only the CMAP/LD trajectory was stable for the entire 30-ns simulation, with a C(alpha) RMSD of approximately 1.4 A, while the PAR22/LD trajectory became unstable early in the simulation, reaching a C(alpha) RMSD of about 2.7 A and remaining at this value until the end of the simulation; the C(alpha) RMSD of the EW/MD simulation was about 1.5 A. The source of the instabilities of the BPTI trajectories in the PAR22/LD simulations was explored by an analysis of the backbone torsion angles. To further validate the findings from this analysis of BPTI, a 35-ns SCP-ISM simulation of Ubiquitin (Ubq) was carried out. For this protein, the CMAP/LD simulation was stable for the entire simulation time (C(alpha) RMSD of approximately 1.0 A), while the PAR22/LD trajectory showed a trend similar to that in BPTI, reaching a C(alpha) RMSD of approximately 1.5 A at 7 ns. All the calculated properties were found to be in agreement with the corresponding experimental values, although local deviations were also observed. HB patterns were also well reproduced by all the continuum solvent simulations with the exception of solvent-exposed side chain-side chain (sc-sc) HB in ProtG, where several of the HB interactions observed in the crystal structure and in the EW/MD simulation were lost. The overall analysis reported in this work suggests that the combination of an atomistic representation of a protein with a CMAP/CHARMM force field and a continuum representation of solvent effects such as the SCP-ISM provides a good description of structural and dynamic properties obtained from long computer simulations. Although the SCP-ISM simulations (CMAP/LD) reported here were shown to be stable and the properties well reproduced, further refinement is needed to attain a level of accuracy suitable for more challenging biological applications, particularly the study of protein-protein interactions.

Semimicroscopic modeling of permeation energetics in ion channels

The semimicroscopic (SMC) approach to modeling the energetics of ion permeation through biological channels provides an alternative perspective to standard molecular dynamics methods. It exploits the timescale separation between electronic and structural contributions to dielectric stabilization and accounts for electronic polarization by embedding the channel in a milieu that, on average, describes this polarization. Ions, water, and selected peptide moieties are mobile and comprise the reorganizational contribution to dielectric stabilization. The conceptual advantages and limitations of the technique are described. Methodological details are outlined, stressing three convenient electrical geometries. Practical aspects of the SMC procedure are explained, highlighting the areas ripe for further development. Finally, some specific applications are considered.