Automated Parameterization of Coarse-Grained Polyethylenimine under a Martini Framework

As a versatile polymer in many applications, synthesized polyethylenimine (PEI) is polydisperse with diverse branched structures that attain pH-dependent protonation states. Understanding the structure-function relationship of PEI is necessary for enhancing its efficacy in various applications. Coarse-grained (CG) simulations can be performed at length and time scales directly comparable with experimental data while maintaining the molecular perspective. However, manually developing CG forcefields for complex PEI structures is time-consuming and prone to human errors. This article presents a fully automated algorithm that can coarse-grain any branched architecture of PEI from its all-atom (AA) simulation trajectories and topology. The algorithm is demonstrated by coarse-graining a branched 2 kDa PEI, which can replicate the AA diffusion coefficient, radius of gyration, and end-to-end distance of the longest linear chain. Commercially available 25 and 2 kDa Millipore-Sigma PEIs are used for experimental validation. Specifically, branched PEI architectures are proposed, coarse-grained using the automated algorithm, and then simulated at different mass concentrations. The CG PEIs can reproduce existing experimental data on PEI's diffusion coefficient and Stokes-Einstein radius at infinite dilution as well as its intrinsic viscosity. This suggests a strategy where probable chemical structures of synthetic PEIs can be inferred computationally using the developed algorithm. The coarse-graining methodology presented here can also be extended to other polymers.

Polycation Architecture Affects Complexation and Delivery of Short Antisense Oligonucleotides: Micelleplexes Outperform Polyplexes

Herein, we examine the complexation and biological delivery of a short single-stranded antisense oligonucleotide (ASO) payload with four polymer derivatives that form two architectural variants (polyplexes and micelleplexes): a homopolymer poly(2-dimethylaminoethyl methacrylate) (D), a diblock polymer poly(ethylene glycol)methylether methacrylate-block-poly(2-dimethylaminoethyl methacrylate) (O_bD), and two micelle-forming variants, poly(2-dimethylaminoethyl methacrylate)-block-poly(n-butyl methacrylate) (DB) and poly(ethylene glycol)methylether methacrylate-block-poly(2-dimethylaminoethyl methacrylate)-block-poly(n-butyl methacrylate) (O_bDB). Both polyplexes and micelleplexes complexed ASOs, and the incorporation of an O_b brush enhances colloidal stability. Micellplexes are templated by the size and shape of the unloaded micelle and that micelle-ASO complexation is not sensitive to formulation/mixing order, allowing ease, versatility, and reproducibility in packaging short oligonucleotides. The DB micelleplexes promoted the largest gene silencing, internalization, and tolerable toxicity while the O_bDB micelleplexes displayed enhanced colloidal stability and highly efficient payload trafficking despite having lower cellular uptake. Overall, this work demonstrates that cationic micelles are superior delivery vehicles for ASOs denoting the importance of vehicle architecture in biological performance.

Coarse-Grained Modeling of Ion-Containing Polymers

Ion-containing polymers have continued to be an important research focus for several decades due to their use as an electrolyte in energy storage and conversion devices. Elucidation of connections between the mesoscopic structure and multiscale dynamics of the ions and solvent remains incompletely understood. Coarse-grained modeling provides an efficient approach for exploring the structural and dynamical properties of these soft materials. The unique physicochemical properties of such polymers are of broad interest. In this review, we summarize the current development and understanding of the structure-property relationship of ion-containing polymers and provide insights into the design of such materials determined from coarse-grained modeling and simulations accompanying significant advances in experimental strategies. We specifically concentrate on three types of ion-containing polymers: proton exchange membranes (PEMs), anion exchange membranes (AEMs), and polymerized ionic liquids (polyILs). We posit that insight into the similarities and differences in these materials will lead to guidance in the rational design of high-performance novel materials with improved properties for various power source technologies.