Automated Parameterization of Coarse-Grained Polyethylenimine under a Martini Framework

As a versatile polymer in many applications, synthesizedpolyethylenimine(PEI) is polydisperse with diverse branched structures that attainpH-dependent protonation states. Understanding the structure-functionrelationship of PEI is necessary for enhancing its efficacy in variousapplications. Coarse-grained (CG) simulations can be performed atlength and time scales directly comparable with experimental datawhile maintaining the molecular perspective. However, manually developingCG forcefields for complex PEI structures is time-consuming and proneto human errors. This article presents a fully automated algorithmthat can coarse-grain any branched architecture of PEI from its all-atom(AA) simulation trajectories and topology. The algorithm is demonstratedby coarse-graining a branched 2 kDa PEI, which can replicate the AAdiffusion coefficient, radius of gyration, and end-to-end distanceof the longest linear chain. Commercially available 25 and 2 kDa Millipore-SigmaPEIs are used for experimental validation. Specifically, branchedPEI architectures are proposed, coarse-grained using the automatedalgorithm, and then simulated at different mass concentrations. TheCG PEIs can reproduce existing experimental data on PEI's diffusioncoefficient and Stokes-Einstein radius at infinite dilutionas well as its intrinsic viscosity. This suggests a strategy whereprobable chemical structures of synthetic PEIs can be inferred computationallyusing the developed algorithm. The coarse-graining methodology presentedhere can also be extended to other polymers.