LigninGraphs: lignin structure determination with multiscale graph modeling

Yifan Wang; Jake Kalscheur; Elvis Ebikade; Qiang Li; Dionisios G Vlachos

doi:10.1186/s13321-022-00627-2

LigninGraphs: lignin structure determination with multiscale graph modeling

J Cheminform. 2022 Jul 6;14(1):43. doi: 10.1186/s13321-022-00627-2.

Authors

Yifan Wang^{1

2}, Jake Kalscheur^{1

2}, Elvis Ebikade^{1

2}, Qiang Li², Dionisios G Vlachos^{3

4}

Affiliations

¹ Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy St, Newark, DE, 19716, USA.
² Catalysis Center for Energy Innovation, RAPID Manufacturing Institute, and Delaware Energy Institute (DEI), University of Delaware, 221 Academy St, Newark, DE, 19716, USA.
³ Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy St, Newark, DE, 19716, USA. vlachos@udel.edu.
⁴ Catalysis Center for Energy Innovation, RAPID Manufacturing Institute, and Delaware Energy Institute (DEI), University of Delaware, 221 Academy St, Newark, DE, 19716, USA. vlachos@udel.edu.

Abstract

Lignin is an aromatic biopolymer found in ubiquitous sources of woody biomass. Designing and optimizing lignin valorization processes requires a fundamental understanding of lignin structures. Experimental characterization techniques, such as 2D-heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra, could elucidate the global properties of the polymer molecules. Computer models could extend the resolution of experiments by representing structures at the molecular and atomistic scales. We introduce a graph-based multiscale modeling framework for lignin structure generation and visualization. The framework employs accelerated rejection-free polymerization and hierarchical Metropolis Monte Carlo optimization algorithms. We obtain structure libraries for various lignin feedstocks based on literature and new experimental NMR data for poplar wood, pinewood, and herbaceous lignin. The framework could guide researchers towards feasible lignin structures, efficient space exploration, and future kinetics modeling. Its software implementation in Python, LigninGraphs, is open-source and available on GitHub.

Keywords: Biomass; Lignin; NMR spectroscopy; Stochastic simulations; Structure optimization.

Abstract

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