SNIC
SUPR
SNIC SUPR
MD and NMR joining forces: Simulations of spectroscopic data to reveal hydration effects in biomacromolecular architectures
Dnr:

SNIC 2018/3-487

Type:

SNAC Medium

Principal Investigator:

Lars Berglund

Affiliation:

Kungliga Tekniska högskolan

Start Date:

2018-10-04

End Date:

2019-11-01

Primary Classification:

10402: Physical Chemistry

Secondary Classification:

10403: Materials Chemistry

Webpage:

Allocation

Abstract

Water constitutes a major limiting factor when it comes to exploiting cellulosic biomaterial in novel applications. The effect of water are ubiquitous but the molecular origins of those effects remain obscure. The project aim is to clarify those molecular origins by combining nuclear magnetic resonance NMR on the experimental side and molecular dynamics simulations MD on the interpretational side. Suitable scattering experiments will provide additional experimental support. The objectives are to tackle the state of water and the state of the macromolecules in a variety of hydrated biomacromolecues such as cellulose, hemicellulose, chitosan and chitin. Where does water reside, and how does water soften macromolecular dynamics? What kind of heterogeneous aggregated structures exist, and on which time and length scales? How are structural and dynamical features influenced by creating mixed architectures with different biomolecular components (that is, in composites)? The standing agenda is joint simulation-aided atomistic-scale interpretation of the experimental data. On the computational side, planned activities are MD simulations that will be performed using established protocols [1-4] of model systems (such as hemicellulose/cellulose interfaces, chitin fibrils and fibril aggregates) at varying hydration. The generated molecular structure and dynamics will be compared directly to experimental data in the form of (i) calculated NMR relaxation times, (ii) calculated static and dynamic structure factors, and (iii) calculated self diffusion of water. Simulated properties are spatially resolved, in the sense that they can be used to interpret experimental data with respect variations in the local chemical environment from, e.g., heterogeneous chemical structure, presence of interfaces, defects in crystal structure, or hydration. Recently, we have shown that MD simulations can quantitatively interpret NMR relaxation data recorded at different levels of hydration [1]. Yet, the truly novel aspect of that work was that the interpretation revealed previously unknown molecular features. It is this that we want to repeat, broaden and improve – we want to open a new window on biomacromolecular behavior. [1] Chen, P. et al., Biomacromolecules, 19:2567-2579 (2018) [2] Berglund, J. et al., Cellulose (2018). https://doi.org/10.1007/s10570-018-1737-z [3] Abad, A. et al., Plant Physiol, 175:1579-1592 (2017) [4] Wang, Y. et al., Comput. Mater. Sci., 128, 191-197 (2017)