Understanding Structure in Methylcellulose Solutions using Machine Learning Enhanced Scattering Analysis (CREASE), Coarse-Grained, and Atomistic Molecular Dynamics Simulations

Methylcellulose (MC) iscellulose derivative in which some of the hydroxyl groups are replaced by methoxy(-OCH3) groups. Aqueous solutions of MC exhibit unique phase behavior wherein at low temperatures MC chains are soluble in water and at high temperatures MC chains assemble into semi-flexible fibrils and fibrillar networks.Fibrillar networks exhibit mechanical and rheological properties that make them useful as food and pharmaceutical ingredients. Structural characterization of MC aqueous solutions through small angle X-ray scattering (SAXS) experiments show that MC fibrils exhibit a consistent fibril diameter with varying MC concentration and molecular weights; however, the molecular underpinnings of this observation are unclear. Our work aims to elucidate these molecular underpinnings using computational techniques from top-down (machine learning enhanced computational reverse engineering analysis of scattering experiments: CREASE) and bottom-up (molecular dynamics simulations). In the top-down approach, (Macromolecules 202255(24), 11076-11091), Wu and Jayaraman found consistent MC fibril diameter distributions using CREASE and analytical model fits, confirming the results by Lodge, Bates, and co-workers (Macromolecules, 2018, 51, 7767−7775) that MC forms fibrils with consistent average diameters of∼15–20 nm regardless of the chain length and concentration of MC chains. In the bottom-up approach,which is the focus of this talk, we use both coarse-grained(CG) and atomistic(AA) molecular dynamics (MD) simulations to capture macromolecular-scale fibril assembly and the molecular-level interactions between MC chains that drive that assembly, respectively. In the CG MD simulations, we observe MC chains assemble in parallel fashion toform fibrils with consistent diameter for varying MC chain length and concentration. Guided by those CG MD chain configurations where solvent is implicit, we use atomistic MD simulations with explicit water, anduncover a potential explanation for the consistent fibril diameter: inter-MC chain twisting. We find that acombination of favorable hydrogen bonds and hydrophobic interactions drives the twisting of MC chains during fibril formation.Our work provides a holistic understanding of MC chains assembly in water and aids material development for application of MC in various industries.