Implicit Solvation Using the Superposition Approximation (IS-SPA): Extension to Peptides in a Polar Solvent.

Efficient, accurate, and adaptable implicit solvent models remain a significant challenge in the field of molecular simulation. A recent implicit solvent model, IS-SPA, based on approximating the mean solvent force using the superposition approximation, provides a platform to achieve these goals. IS-SPA was originally developed to handle nonpolar solutes in a polar solvent and did not accurately capture polar solvation. Here, we demonstrate that IS-SPA can accurately capture polar solvation by incorporating solvent orientation and accounting for the contributions from long ranged electrostatics. Solvent orientation is approximated as that of an ideal dipole aligned in a mean electrostatic field and an analytic form of the long ranged electrostatics is derived. Parameters for the model are calculated from explicit solvent simulations of an isolated atom or molecule and include atom-based solvent densities, mean electric field functions, radially symmetric averaged Lennard-Jones forces, and multipoles of the explicit solvent model. Using these parameters, IS-SPA accounts for asymmetry of charge solvation and reproduces the explicit solvent potential of mean force of dimerization of two oppositely charged Lennard-Jones spheres in chloroform with high fidelity. Additionally, the model more accurately captures the effect of explicit solvent on the monomer and dimer configurations of alanine dipeptide in chloroform than a generalized Born or constant density dielectric model. The current version of the algorithm is expected to outperform explicit solvent simulations for aggregation of small peptides at concentrations below 150 mM, well above the typical experimental concentrations for these materials.

Residue-Level Allostery Propagates through the Effective Coarse-Grained Hessian.

The long-ranged coupling between residues that gives rise to allostery in a protein is built up from short-ranged physical interactions. Computational tools used to predict this coupling and its functional relevance have relied on the application of graph theoretical metrics to residue-level correlations measured from all-atom molecular dynamics simulations. The short-ranged interactions that yield these long-ranged residue-level correlations are quantified by the effective coarse-grained Hessian. Here we compute an effective harmonic coarse-grained Hessian from simulations of a benchmark allosteric protein, IGPS, and demonstrate the improved locality of this graph Laplacian over two other connectivity matrices. Additionally, two centrality metrics are developed that indicate the direct and indirect importance of each residue at producing the covariance between the effector binding pocket and the active site. The residue importance indicated by these two metrics is corroborated by previous mutagenesis experiments and leads to unique functional insights; in contrast to previous computational analyses, our results suggest that fP76-hK181 is the most important contact for conveying direct allosteric paths across the HisF-HisH interface. The connectivity around fD98 is found to be important at affecting allostery through indirect means.

Initial Aggregation and Ordering Mechanism of Diphenylalanine from Microsecond All-Atom Molecular Dynamics Simulations.

Self-assembled diphenylalanine (FF) nanostructures have recently been demonstrated to be interesting materials for antibacterial and anticancer applications. These applications, among others, seek to take advantage of the high-order and resulting appealing physical properties of FF nanostructures by modifying the peptide in some way to achieve specific functionality. To rationally design modifications to the dipeptide that allow for this behavior, the driving forces of FF self-assembly must be understood. Molecular simulations have been utilized to assess these properties but have yielded conflicting conclusions due to inconsistencies in models chosen as well as the lack of quantitative analyses on the specific driving forces. Here, we present an all-atom explicit solvent molecular dynamics-based study on different length scales of FF aggregation. We utilize a free energy decomposition analysis as well as a dimer cluster analysis to identify the initial aggregation driving force to be FF intermolecular electrostatics, whereas solvent-mediated forces drive crystal growth. These data are consistent with the hypothesis that all hydrophobic dipeptides will have a similar initial aggregation mechanism until a critical aggregate size is reached, at which point crystallization occurs and subsequent crystal growth is dominated by solvent-mediated forces. We demonstrate that this proposed mechanism is testable by infrared spectroscopy focusing on the blueshift of the amide I peak as well as the ordering of the carboxylate peak.

Elucidating Structural Evolution of Perylene Diimide Aggregates Using Vibrational Spectroscopy and Molecular Dynamics Simulations.

Perylene diimides (PDIs) are a family of molecules that have potential applications to organic photovoltaics. These systems typically aggregate cofacially due to π-stacking interactions between the aromatic perylene cores. In this study, the structure and characteristics of aggregated N, N'-bis(2,6-diisopropylphenyl)-3,4,9,10-perylenetetracarboxylic diimide (common name lumogen orange), a perylene diimide (PDI) with sterically bulky imide functional groups, were investigated using both experimental vibrational spectroscopy and molecular dynamics (MD) simulations. Samples of lumogen orange dispersed in chloroform exhibited complex aggregation behavior, as evidenced by the evolution of the FTIR spectrum over a period of several hours. While for many PDI systems with less bulky imide functional groups aggregation is dominated by π-stacking interactions between perylene cores, MD simulations of lumogen orange dimers indicated a second, more energetically favorable aggregate structure mediated by "edge-to-edge" interactions between PDI units. Two-dimensional infrared spectroscopy together with orientational statistics obtained from MD simulations were employed to identify and rationalize aggregation-induced coupling between vibrational modes.

Implicit Solvation Using the Superposition Approximation (IS-SPA): An Implicit Treatment of the Nonpolar Component to Solvation for Simulating Molecular Aggregation.

Nonpolar solute-solvent interactions are the driving force for aggregation in important chemical and biological phenomena including protein folding, peptide self-assembly, and oil-water emulsion formation. Currently, the most accurate and computationally efficient description of these processes requires an explicit treatment of all solvent and solute atoms. Previous computationally feasible implicit solvent models, such as solute surface area approaches, are unsuccessful at capturing aggregation features including both structural and energetic trends while more theoretically rigorous approaches, such as Reference Interaction Site Model (RISM), are accurate but extremely computationally demanding. Our approach, denoted Implicit Solvation using the Superposition Approximation (IS-SPA), builds on previous theory utilizing the Kirkwood superposition approximation to approximate the mean force of the solvent from solute parameters. We introduce and verify a parabolic first solvation shell truncation of atomic solvation, fitting water distributions around a molecule, and a Monte Carlo integration of the mean solvent force. These extensions allow this method to be implemented as an efficient nonpolar implicit solvent model for molecular simulation. The approximations in IS-SPA are first explored and justified for the homodimerization of an array of different sized Lennard-Jones spheres. The accuracy and transferability of the approach are demonstrated by its ability to capture the position and relative energies of the desolvation barrier and free energy minimum of alkane homodimers. The model is then shown to reproduce the phase separation and solubility of cyclohexane and water. These promising results, coupled with 2 orders of magnitude speed-up for dilute systems as compared to explicit solvent simulations, demonstrate that IS-SPA is an appealing approach to boost the time- and length-scale of molecular aggregation simulations.

Deriving Coarse-Grained Charges from All-Atom Systems: An Analytic Solution.

An analytic method to assign optimal coarse-grained charges based on electrostatic potential matching is presented. This solution is the infinite size and density limit of grid-integration charge-fitting and is computationally more efficient by several orders of magnitude. The solution is also minimized with respect to coarse-grained positions which proves to be an extremely important step in reproducing the all-atom electrostatic potential. The joint optimal-charge optimal-position coarse-graining procedure is applied to a number of aggregating proteins using single-site per amino acid resolution. These models provide a good estimate of both the vacuum and Debye-Hückel screened all-atom electrostatic potentials in the vicinity and in the far-field of the protein. Additionally, these coarse-grained models are shown to approximate the all-atom dimerization electrostatic potential energy of 10 aggregating proteins with good accuracy.