Stochastic Model of Lignocellulosic Material Saccharification
Eric Behle, Ad\'ela\"ide Raguin

TL;DR
This paper introduces a stochastic computational model simulating lignocellulosic biomass saccharification, revealing the significant influence of substrate crystallinity over hemicellulose content on enzymatic breakdown efficiency.
Contribution
It presents a novel stochastic simulation approach using Gillespie algorithm to model biomass saccharification, incorporating substrate structure and enzyme interactions, validated against experimental data.
Findings
Crystallinity impacts saccharification yield more than hemicellulose content.
The model accurately reproduces experimental saccharification time courses.
Hemicellulose content is less influential than previously thought.
Abstract
The processing of agricultural wastes towards extraction of renewable resources is recently being considered as a promising alternative to conventional biofuel production processes. Agricultural residues represent an abundant and unexploited raw material that intrinsically contains chemical energy in the form of polysaccharides. The degradation procedure is a complex chemical process that is currently time intensive and costly. Various pre-treatment methods are being investigated to determine the subsequent modification of the material and the main obstacles in increasing the enzymatic saccharification yield. In this study, we present a computational model that complements the experimental approaches. We decipher how the three-dimensional structure of the substrate impacts the saccharification yield. We model a cell wall microfibril composed of cellulose and surrounded by hemicellulose…
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