Extracting Aggregation Free Energies of Mixed Clusters from Simulations of Small Systems: Application to Ionic Surfactant Micelles

Breakdown of Langmuir Adsorption Isotherm in Small Closed Systems

For more than a century, monolayer adsorptions in which adsorbate molecules and adsorbing sites behave ideally have been successfully described by Langmuir's adsorption isotherm. For example, the amount of adsorbed material, as a function of concentration of the material which is not adsorbed, obeys Langmuir's equation. In this paper, we argue that this relation is valid only for macroscopic systems. However, when particle numbers of adsorbate molecules and/or adsorbing sites are small, Langmuir's model fails to describe the chemical equilibrium of the system. This is because the kinetics of forming, or the probability of observing, occupied sites arises from two-body interactions, and as such, ought to include cross-correlations between particle numbers of the adsorbate and adsorbing sites. The effect of these correlations, as reflected by deviations in predicting composition when correlations are ignored, increases with decreasing particle numbers and becomes substantial when only few adsorbate molecules, or adsorbing sites, are present in the system. In addition, any change that augments the fraction of occupied sites at equilibrium (e.g., smaller volume, lower temperature, or stronger adsorption energy) further increases the discrepancy between observed properties of small systems and those predicted by Langmuir's theory. In contrast, for large systems, these cross-correlations become negligible, and therefore when expressing properties involving two-body processes, it is possible to consider independently the concentration of each component. By applying statistical mechanics concepts, we derive a general expression of the equilibrium constant for adsorption. It is also demonstrated that in ensembles in which total numbers of particles are fixed, the magnitudes of fluctuations in particle numbers alone can predict the average chemical composition of the system. Moreover, an alternative adsorption equation, predicting the average fraction of occupied sites from the value of the equilibrium constant, is proposed. All derived relations were tested against results obtained by Monte Carlo simulations.

Finite-Size Effects in Simulations of Peptide/Lipid Assembly

Abstract

Molecular dynamics simulations are an attractive tool for understanding lipid/peptide self-assembly but can be plagued by inaccuracies when the system sizes are too small. The general guidance from self-assembly simulations of homogeneous micelles is that the total number of surfactants should be three to five times greater than the equilibrium aggregate number of surfactants per micelle. Herein, the heuristic is tested on the more complicated self-assembly of lipids and amphipathic peptides using the Cooke and Martini 3 coarse-grained models. Cooke model simulations with 50 to 1000 lipids and no peptide are dominated by finite-size effects, with usually one aggregate (micelle or nanodisc) containing most of the lipids forming at each system size. Approximately 200 systems of different peptide/lipid (P/L) ratios and sizes of up to 1000 lipids yield a “finite-size phase diagram” for peptide driven self-assembly, including a coexistence region of micelles and discs. Insights from the Cooke model are applied to the assembly of dimyristoylphosphatidylcholine and the ELK-neutral peptide using the Martini 3 model. Systems of 150, 450, and 900 lipids with P/L = 1/6.25 form mixtures of lipid-rich discs that agree in size with experiment and peptide-rich micelles. Only the 150-lipid system shows finite-size effects, which arise from the long-tailed distribution of aggregate sizes. The general rule of three to five times the equilibrium aggregate size remains a practical heuristic for the Cooke and Martini 3 systems investigated here.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s00232-022-00255-9.

Binding reactions at finite systems

A perpetual yearn exists among computational scientists to scale down the size of physical systems, a desire shared as well with experimentalists able to track single molecules. A question then arises whether averages observed at small systems are the same as those observed at large or macroscopic systems. Utilizing statistical-mechanics formulations in ensembles in which the total numbers of particles are fixed, we demonstrate that properties of binding reactions are not homogeneous functions. This means that averages of intensive parameters, such as the concentration of the bound-state, at finite systems are different than those at large systems. The discrepancy increases with decreasing temperature, volume, and to some extent, numbers of particles. As perplexing as it may sound, despite variations in average quantities, extracting the equilibrium constant from systems of different sizes does yield the same value. The reason is that correlations in reactants' concentrations ought to be accounted for in the expression of the equilibrium constant, being negligible at large-scale but significant at small-scale. Similar arguments pertain to the calculations of the reaction rate constants, more specifically, the bimolecular rate of the forward reaction is related to the average of the product (and not to the product of the averages) of the reactants' concentrations. Furthermore, we derive relations aiming to predict the composition only from the equilibrium constant and the system's size. All predictions are validated by Monte-Carlo and molecular dynamics simulations. An important consequence of these findings is that the expression of the equilibrium constant at finite systems is not dictated solely by the chemical equation of the reaction but requires knowledge of the elementary processes involved.

Free energy of micellization of dodecyl phosphocholine (DPC) from molecular simulation: Hybrid PEACH-BAR method

A new method to extract the free energy of aggregation versus aggregate size from molecular simulation data is proposed and applied to a united atom model of the zwitterionic surfactant dodecyl phosphocholine in water. This system's slow dissociation rate and low critical micelle concentration (CMC of approximately 1-2 mM) make extraction of cluster free energies directly from simulation results using the "partition-enabled analysis of cluster histogram" (PEACH) method impractical. The new approach applies PEACH to a model with weakened attractions between aggregants, which allows sampling of a continuous range of cluster sizes, then recovers the free energy of aggregation under the original fully-attractive force field using the BAR free energy difference method. PEACH-BAR results are compared with free energy differences calculated via umbrella sampling, and are used to make predictions of CMC, average cluster size, and SAXS scattering profiles that are in fair agreement with experiment.

Mesostructuring in Liquid-Liquid Extraction Organic Phases Originating from Critical Points

Organic phase structure plays an important role in solute extraction energetics and phase behavior of liquid-liquid extraction (LLE) systems. For a binary extractant (amphiphile)/solvent mixture of relevance to LLE, we find that the organic phase mesostructuring is consistent with extractant concentration fluctuations as the compositional isotherm traverses the Widom line above its liquid-liquid critical point. This reveals a different mechanism for the well-documented heterogeneities in LLE organic phases that are typically attributed to micellization.

Finite-Size Effects and Optimal System Sizes in Simulations of Surfactant Micelle Self-Assembly

The spontaneous formation of micelles in aqueous solutions is governed by the amphipathic nature of surfactants and is practically interesting due to the regular use of micelles as membrane mimics, for the characterization of protein structure, and for drug design and delivery. We performed a systematic characterization of the finite-size effect observed in single-component dodecylphosphocholine (DPC) micelles with the coarse-grained MARTINI model. Of multiple coarse-grained solvent models investigated using large system sizes, the nonpolarizable solvent model was found to most accurately reproduce SANS spectra of 100 mM DPC in aqueous solution. We systematically investigated the finite-size effect at constant 100 mM concentration in 23 systems of sizes 40-150 DPC, confirming the finite-size effect to manifest as an oscillation in the mean micelle aggregation number about the thermodynamic aggregation number as the system size increases. The oscillations in aggregation number mostly diminish once the system supports the formation of three micelles. Similar oscillations were observed in the estimated critical micelle concentration with a mean value of 1.10 mM, which is in agreement with experiment to 0.1 mM. The accuracy of using a multiscale simulation approach to avoid finite-size effects in the micelle size distribution and SANS spectra using MARTINI and CHARMM36 was explored using multiple long time scale 500 DPC coarse-grained simulations, which were back-mapped to CHARMM36 all-atom systems. It was found that the MARTINI model generally occupies more volume than the all-atom model, leading to the formation of micelles that are of a reasonable radius of gyration but are smaller in aggregation number. The systematic characterization of the finite-size effect and exploration of multiscale modeling presented in this work provide guidance for the accurate modeling of micelles in simulations.

Hierarchical phenomena in multicomponent liquids: simulation methods, analysis, chemistry

Complex, multicomponent, solutions have often been studied solely through the lens of specific applications of interest. Yet advances to both simulation methodologies (enhanced sampling, etc.) and analysis techniques (network analysis algorithms and others), are creating a trove of data that reveal transcending characteristics across vast compositional phase space. This perspective discusses technical considerations of the reliable and accurate simulations of complex solutions, followed by the advances to analysis algorithms that elucidate coupling of different length and timescale behavior (hierarchical phenomena). The different manifestations of hierarchical phenomena are presented across an array of solution environments, emphasizing fundamental and ongoing science questions. With a more advanced molecular understanding in hand, a quintessential application (solvent extraction) is discussed, where significant opportunities exist to re-imagine the technical scope of an established technology.