Biomacromolecules rely on the precise placement of monomers to encode information for structure, function, and physiology. Efforts to emulate this complexity via the synthetic control of chemical sequence in polymers are finding success; however, there is little understanding of how to translate monomer sequence to physical material properties. Here we establish design rules for implementing this sequence-control in materials known as complex coacervates. These materials are formed by the associative phase separation of oppositely charged polyelectrolytes into polyelectrolyte dense (coacervate) and polyelectrolyte dilute (supernatant) phases. We demonstrate that patterns of charges can profoundly affect the charge–charge associations that drive this process. Furthermore, we establish the physical origin of this pattern-dependent interaction: there is a nuanced combination of structural changes in the dense coacervate phase and a 1D confinement of counterions due to patterns along polymers in the supernatant phase.
Our ability to predict the thermodynamic phase behavior of a material system is a direct reflection on our understanding of the relevant interactions. Voorn−Overbeek (VO) theory, which combines Flory−Huggins polymer mixing with Debye−Huckel electrostatics, has been used to describe the associative liquid−liquid phase separation phenomenon known as complex coacervation since the 1950s. The long-standing utility of this theory stems from its simplicity coupled with its apparent agreement with physical systems. VO theory has also served as the starting point for a large class of field theories that predict similar phase behaviors. Recent work using new hybrid simulation methods demonstrates novel coacervate-driven self-assembly is strongly affected by molecular details. Liquid state (LS) theory suggests there are fundamental reasons for this observation and that agreement between VO and experiment is fortuitous. It is hypothesized that VO/experimental matching is due to a cancellation of errors arising from the neglect of monomer-level charge connectivity and excluded volume effects. In this article, we use Monte Carlo (MC) simulations to confirm the earlier predictions from LS theory. We directly observe effects related to connectivity-driven charge correlations. We also observe strong exclusion of salt from the polymer-rich coacervate phase, in direct opposition with VO theory and in near quantitative agreement with experimental results. Strikingly, a comparison of predicted phase diagrams using identical system parameters shows that VO overpredicts coacervate phase behavior and that previous agreement with experiments was likely due to the use of unphysical fitting parameters. This work provides new insights into the mechanisms driving complex coacervation and shows promise for predicting coacervate phase behavior based on resolving molecular level charge structure.
Oppositely charged polyelectrolytes in aqueous solution can undergo associative phase separation into a liquid-like complex coacervate phase that is polyelectrolyte-rich and an aqueous supernatant phase that is polyelectrolyte-deficient. This same complex coacervation motif can be used to drive self-assembly of block copolyelectrolytes via electrostatic interactions and can be controlled using e.g. ionic strength, pH, temperature, and polymer architecture. While there has been a large amount of research studying this self-assembly, the ability of theory to accurately capture the disparate length scales that govern the appropriate physics is limited. This is especially true when the coacervates have a high charge density; examples include biopolymers such as heparin or DNA as well as synthetic polymers such as poly(styrenesulfonate) or poly(acrylic acid). We incorporate molecular-level Monte Carlo simulations into single chain in mean field simulations, leading to a multiscale, coarse-grained description of such systems. These two length scales are connected using standard Widom insertion methods at the molecular Monte Carlo level, which provides the thermodynamic information needed to construct free energy landscapes used in the single chain in mean field calculations necessary to understand coacervate-driven self-assembly. We compare the results of our simulations to classical theories of complex coacervation and experiment. Our method demonstrates interesting behaviors in coacervate-forming diblock copolyectrolytes that reflect molecular details included into the model, such as morphological coexistence, interfacial excess of salt, and counterintuitive salt-induced ordering.
We study the effects of confinement and hydrophobicity of a spherical cavity on the structural and thermal stability of proteins in the framework of a hydrophobic-polar (HP) lattice model. We observe that a neutral confinement stabilizes the folded state of the protein by eliminating many of the open-chain conformations of the unfolded state. Hydrophobic confinement always destabilizes the protein because of protein-surface interactions. However, for moderate surface hydrophobicities, the protein remains stabilized relative to its state in free solution because of the dominance of entropic effects. These results are consistent with our experimental findings of (a) enhanced activity of alcohol dehydrogenase (ADH) when immobilized inside the essentially cylindrical pores of hydrophilic mesoporous silica (SBA-15) and (b) unaffected activity when immobilized inside weakly hydrophobic pores of methacrylate resin compared to its activity in free solution. In the same vein, our predictions are also consistent with the behavior of lysozyme and myoglobin in hydrophilic and hydrophobic SBA-15, which show qualitatively the same trends. Apparently, our results have validity across these very different enzymes, and we therefore suggest that confinement can be used to selectively improve enzyme performance.
AIEgens = Aggregation-induced-emission luminogens.Supporting information and the ORCID identification number(s) for the author(s) of this articlecan be found under: https://doi.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.