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

How do water-mediated interactions and osmotic second virial coefficients vary with particle size?

We examine quantitatively the solute-size dependences of the effective interactions between nonpolar solutes in water and in a simple liquid. The potential w(r) of mean force and the osmotic second virial coefficients B are calculated with high accuracy from molecular dynamics simulations. As the solute diameter increases from methane's to C60's with the solute-solute and solute-solvent attractive interaction parameters fixed to those for the methane-methane and methane-water interactions, the first minimum of w(r) lowers from -1.1 to -4.7 in units of the thermal energy kT. Correspondingly, the magnitude of B (<0) increases proportional to σα with some power close to 6 or 7, which reinforces the solute-size dependence of B found earlier for a smaller range of σ [H. Naito, R. Okamoto, T. Sumi and K. Koga, J. Chem. Phys., 2022, 156, 221104]. We also demonstrate that the strength of the attractive interactions between solute and solvent molecules can qualitatively change the characteristics of the effective pair interaction between solute particles, both in water and in a simple liquid. If the solute-solvent attractive force is set to be weaker (stronger) than a threshold, the effective interaction becomes increasingly attractive (repulsive) with increasing solute size.

Micellar Composition Affects Lipid Accretion Kinetics in Molecular Dynamics Simulations: Support for Lipid Network Reproduction

Mixed lipid micelles were proposed to facilitate life through their documented growth dynamics and catalytic properties. Our previous research predicted that micellar self-reproduction involves catalyzed accretion of lipid molecules by the residing lipids, leading to compositional homeostasis. Here, we employ atomistic Molecular Dynamics simulations, beginning with 54 lipid monomers, tracking an entire course of micellar accretion. This was done to examine the self-assembly of variegated lipid clusters, allowing us to measure entry and exit rates of monomeric lipids into pre-micelles with different compositions and sizes. We observe considerable rate-modifications that depend on the assembly composition and scrutinize the underlying mechanisms as well as the energy contributions. Lastly, we describe the measured potential for compositional homeostasis in our simulated mixed micelles. This affirms the basis for micellar self-reproduction, with implications for the study of the origin of life.

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.

Direct Comparison of Amino Acid and Salt Interactions with Double-Stranded and Single-Stranded DNA from Explicit-Solvent Molecular Dynamics Simulations

Given the ubiquitous nature of protein-DNA interactions, it is important to understand the interaction thermodynamics of individual amino acid side chains for DNA. One way to assess these preferences is to perform molecular dynamics (MD) simulations. Here we report MD simulations of 20 amino acid side chain analogs interacting simultaneously with both a 70-base-pair double-stranded DNA and with a 70-nucleotide single-stranded DNA. The relative preferences of the amino acid side chains for dsDNA and ssDNA match well with values deduced from crystallographic analyses of protein-DNA complexes. The estimated apparent free energies of interaction for ssDNA, on the other hand, correlate well with previous simulation values reported for interactions with isolated nucleobases, and with experimental values reported for interactions with guanosine. Comparisons of the interactions with dsDNA and ssDNA indicate that, with the exception of the positively charged side chains, all types of amino acid side chain interact more favorably with ssDNA, with intercalation of aromatic and aliphatic side chains being especially notable. Analysis of the data on a base-by-base basis indicates that positively charged side chains, as well as sodium ions, preferentially bind to cytosine in ssDNA, and that negatively charged side chains, and chloride ions, preferentially bind to guanine in ssDNA. These latter observations provide a novel explanation for the lower salt dependence of DNA duplex stability in GC-rich sequences relative to AT-rich sequences.

Quantifying the Influence of the Crowded Cytoplasm on Small Molecule Diffusion

Cytosolic crowding can influence the thermodynamics and kinetics of in vivo chemical reactions. Most significantly, proteins and nucleic acid crowders reduce the accessible volume fraction, ϕ, available to a diffusing substrate, thereby reducing its effective diffusion rate, Deff, relative to its rate in bulk solution. However, Deff can be further hindered or even enhanced, when long-range crowder/diffuser interactions are significant. To probe these effects, we numerically estimated Deff values for small, charged molecules in representative, cytosolic protein lattices up to 0.1 × 0.1 × 0.1 μm(3) in volume via the homogenized Smoluchowski electro-diffusion equation. We further validated our predictions against Deff estimates from ϕ-dependent analytical relationships, such as the Maxwell-Garnett (MG) bound, as well as explicit solutions of the time-dependent electro-diffusion equation. We find that in typical, moderately crowded cell cytoplasm (ϕ ≈ 0.8), Deff is primarily determined by ϕ; in other words, diverse protein shapes and heterogeneous distributions only modestly impact Deff. However, electrostatic interactions between diffusers and crowders, particularly at low electrolyte ionic strengths, can substantially modulate Deff. These findings help delineate the extent that cytoplasmic crowders influence small molecule diffusion, which ultimately may shape the efficiency and timing of intracellular signaling pathways. More generally, the quantitative agreement between computationally expensive solutions of the time-dependent electro-diffusion equation and its comparatively cheaper homogenized form suggest that the latter is a broadly effective model for diffusion in wide-ranging, crowded biological media.

Shedding light on the hydrophobicity puzzle

A general theory of hydrophobic hydration and pairwise hydrophobic interaction has been developed in the last years. The main ingredient is the recognition that: (a) cavity creation (necessary to insert a solute molecule into water) causes a solvent-excluded volume effect that leads to a loss in the translational entropy of water molecules; (b) the merging of two cavities (necessary to form the contact minimum configuration of two nonpolar molecules) causes a decrease in the solvent-excluded volume effect and so an increase in the translational entropy of water molecules. The performance of the theoretical approach is tested by reproducing both the hydration thermodynamics of xenon and the thermodynamics associated with the formation of the contact minimum configuration of two xenon atoms, over a large temperature range.

Parametrization of Backbone Flexibility in a Coarse-Grained Force Field for Proteins (COFFDROP) Derived from All-Atom Explicit-Solvent Molecular Dynamics Simulations of All Possible Two-Residue Peptides

Recently, we reported the parametrization of a set of coarse-grained (CG) nonbonded potential functions, derived from all-atom explicit-solvent molecular dynamics (MD) simulations of amino acid pairs and designed for use in (implicit-solvent) Brownian dynamics (BD) simulations of proteins; this force field was named COFFDROP (COarse-grained Force Field for Dynamic Representations Of Proteins). Here, we describe the extension of COFFDROP to include bonded backbone terms derived from fitting to results of explicit-solvent MD simulations of all possible two-residue peptides containing the 20 standard amino acids, with histidine modeled in both its protonated and neutral forms. The iterative Boltzmann inversion (IBI) method was used to optimize new CG potential functions for backbone-related terms by attempting to reproduce angle, dihedral, and distance probability distributions generated by the MD simulations. In a simple test of the transferability of the extended force field, the angle, dihedral, and distance probability distributions obtained from BD simulations of 56 three-residue peptides were compared to results from corresponding explicit-solvent MD simulations. In a more challenging test of the COFFDROP force field, it was used to simulate eight intrinsically disordered proteins and was shown to quite accurately reproduce the experimental hydrodynamic radii (Rhydro), provided that the favorable nonbonded interactions of the force field were uniformly scaled downward in magnitude. Overall, the results indicate that the COFFDROP force field is likely to find use in modeling the conformational behavior of intrinsically disordered proteins and multidomain proteins connected by flexible linkers.

COFFDROP: A Coarse-Grained Nonbonded Force Field for Proteins Derived from All-Atom Explicit-Solvent Molecular Dynamics Simulations of Amino Acids

We describe the derivation of a set of bonded and nonbonded coarse-grained (CG) potential functions for use in implicit-solvent Brownian dynamics (BD) simulations of proteins derived from all-atom explicit-solvent molecular dynamics (MD) simulations of amino acids. Bonded potential functions were derived from 1 μs MD simulations of each of the 20 canonical amino acids, with histidine modeled in both its protonated and neutral forms; nonbonded potential functions were derived from 1 μs MD simulations of every possible pairing of the amino acids (231 different systems). The angle and dihedral probability distributions and radial distribution functions sampled during MD were used to optimize a set of CG potential functions through use of the iterative Boltzmann inversion (IBI) method. The optimized set of potential functions—which we term COFFDROP (COarse-grained Force Field for Dynamic Representation Of Proteins)—quantitatively reproduced all of the “target” MD distributions. In a first test of the force field, it was used to predict the clustering behavior of concentrated amino acid solutions; the predictions were directly compared with the results of corresponding all-atom explicit-solvent MD simulations and found to be in excellent agreement. In a second test, BD simulations of the small protein villin headpiece were carried out at concentrations that have recently been studied in all-atom explicit-solvent MD simulations by Petrov and Zagrovic (PLoS Comput. Biol.2014, 5, e1003638). The anomalously strong intermolecular interactions seen in the MD study were reproduced in the COFFDROP simulations; a simple scaling of COFFDROP’s nonbonded parameters, however, produced results in better accordance with experiment. Overall, our results suggest that potential functions derived from simulations of pairwise amino acid interactions might be of quite broad applicability, with COFFDROP likely to be especially useful for modeling unfolded or intrinsically disordered proteins.

Recent advances in transferable coarse-grained modeling of proteins

Computer simulations are indispensable tools for studying the structure and dynamics of biological macromolecules. Biochemical processes occur on different scales of length and time. Atomistic simulations cannot cover the relevant spatiotemporal scales at which the cellular processes occur. To address this challenge, coarse-grained (CG) modeling of the biological systems is employed. Over the last few years, many CG models for proteins continue to be developed. However, many of them are not transferable with respect to different systems and different environments. In this review, we discuss those CG protein models that are transferable and that retain chemical specificity. We restrict ourselves to CG models of soluble proteins only. We also briefly review recent progress made in the multiscale hybrid all-atom/CG simulations of proteins.

Lipid-modified polyethylenimine-mediated DNA attraction evaluated by molecular dynamics simulations

The effect of lipid modification on polyethylenimine (PEI)-mediated DNA attraction was studied by performing umbrella sampling molecular dynamics simulations that involved PEIs modified with three different types of lipids: oleic acid (OA), linoleic acid (LA), and caprylic acid (CA). The potential of mean force between two DNA molecules in the presence of these lipid-modified PEIs was calculated using the weighted histogram analysis method, and it predicted the stability and size of the DNA aggregate. When compared to native PEI, lipid modification was found to enhance the stability of DNA aggregation in the case of long lipids (LA and OA) but reduce the stability in the case of a short lipid (CA). In addition, LA-substituted PEI was shown to form stronger DNA aggregate than OA-substituted PEI, which correlates positively with previous experimental observations.

Molecular dynamics simulations of highly crowded amino acid solutions: comparisons of eight different force field combinations with experiment and with each other

Although it is now commonly accepted that the highly crowded conditions encountered inside biological cells have the potential to significantly alter the thermodynamic properties of biomolecules, it is not known to what extent the thermodynamics of fundamental types of interactions such as salt bridges and hydrophobic interactions are strengthened or weakened by high biomolecular concentrations. As one way of addressing this question we have performed a series of all-atom explicit solvent molecular dynamics (MD) simulations to investigate the effect of increasing solute concentration on the behavior of four types of zwitterionic amino acids in aqueous solution. We have simulated systems containing glycine, valine, phenylalanine or asparagine at concentrations of 50, 100, 200 and 300 mg/ml. Each molecular system has been simulated for 1 μs in order to obtain statistically converged estimates of thermodynamic parameters, and each has been conducted with 8 different force fields and water models; the combined simulation time is 128 μs. The density, viscosity, and dielectric increments of the four amino acids calculated from the simulations have been compared to corresponding experimental measurements. While all of the force fields perform well at reproducing the density increments, discrepancies for the viscosity and dielectric increments raise questions both about the accuracy of the simulation force fields and, in certain cases, the experimental data. We also observe large differences between the various force fields' descriptions of the interaction thermodynamics of salt bridges and, surprisingly, these differences also lead to qualitatively different predictions of their dependences on solute concentration. For the aliphatic interactions of valine sidechains, fewer differences are observed between the force fields, but significant differences are again observed for aromatic interactions of phenylalanine sidechains. Taken together, the results highlight the potential power of using explicit-solvent simulation methods to understand behavior in concentrated systems but also hint at potential difficulties in using these methods to obtain consistent views of behavior in intracellular environments.

Reaching new levels of realism in modeling biological macromolecules in cellular environments

An increasing number of studies are aimed at modeling cellular environments in a comprehensive and realistic fashion. A major challenge in these efforts is how to bridge spatial and temporal scales over many orders of magnitude. Furthermore, there are additional challenges in integrating different aspects ranging from questions about biomolecular stability in crowded environments to the description of reactive processes on cellular scales. In this review, recent studies with models of biomolecules in cellular environments at different levels of detail are discussed in terms of their strengths and weaknesses. In particular, atomistic models, implicit representations of cellular environments, coarse-grained and spheroidal models of biomolecules, as well as the inclusion of reactive processes via reaction-diffusion models are described. Furthermore, strategies for integrating the different models into a comprehensive description of cellular environments are discussed.

A molecular dynamics simulation study on the effect of lipid substitution on polyethylenimine mediated siRNA complexation

Polycations have been explored as non-viral carriers for effective delivery of small interfering RNA (siRNA). Modifying polycations such as polyethylenimine (PEI) with lipid substitution was found to improve the siRNA delivery efficiency of polycationic carriers. However, the role of such lipid modification is not clear and remains to be probed at the atomistic level. In this work, we elucidate the role of lipid modification through a series of all-atom molecular dynamics simulations on siRNA complexation mediated by a native PEI and four analogous obtained by different lipid modifications. The lipid modification does not affect PEI's capability of neutralizing the siRNA charge, neither does it affect the polyion bridging which plays an important role in siRNA complexation. Significant linkages among the lipid modified PEIs via association of lipid side-groups are observed and this results in more stable and compact PEI/siRNA polyplexes. The lipid associations between short lipids form and break frequently while the lipid associations between long lipids are more stable. For PEIs modified with short lipids, increasing the lipid substitution level results in more compact and stable siRNA structure. For PEIs modified with long lipids, increasing the lipid substitution does not change the amount of PEI linkage via lipid association, and has a reverse effect on compacting siRNA structure due to increased steric hindrance brought by the lipid association on individual PEIs. The simulation results generally correlate well with experimental data and suggest a framework of designing and systematic evaluation of polycation-based siRNA carriers using molecular dynamics simulations.

Spatial simulations in systems biology: from molecules to cells

Cells are highly organized objects containing millions of molecules. Each biomolecule has a specific shape in order to interact with others in the complex machinery. Spatial dynamics emerge in this system on length and time scales which can not yet be modeled with full atomic detail. This review gives an overview of methods which can be used to simulate the complete cell at least with molecular detail, especially Brownian dynamics simulations. Such simulations require correct implementation of the diffusion-controlled reaction scheme occurring on this level. Implementations and applications of spatial simulations are presented, and finally it is discussed how the atomic level can be included for instance in multi-scale simulation methods.