Revisiting Theoretical Tools and Approaches for the Valorization of Recalcitrant Lignocellulosic Biomass to Value-Added Chemicals

Abstract

Biorefinery processes for converting lignocellulosic biomass to fuels and chemicals proceed via an integrated series of steps. Biomass is first pretreated and deconstructed using chemical catalysts and/or enzymes to liberate sugar monomers and lignin fragments. Deconstruction is followed by a conversion step in which engineered host organisms assimilate the released sugar monomers and lignin fragments, and produce value-added fuels and chemicals. Over the past couple of decades, a significant amount of work has been done to develop innovative biomass deconstruction and conversion processes that efficiently solubilize biomass, separate lignin from the biomass, maximize yields of bioavailable sugars and lignin fragments and convert the majority of these carbon sources into fuels, commodity chemicals, and materials. Herein, we advocate that advanced in silico approaches provide a theoretical framework for developing efficient processes for lignocellulosic biomass valorization and maximizing yields of sugars and lignin fragments during deconstruction and fuel and chemical titers during conversion. This manuscript surveys the latest developments in lignocellulosic biomass valorization with special attention given to highlighting computational approaches used in process optimization for lignocellulose pretreatment; enzyme engineering for enhanced saccharification and delignification; and prediction of the genome modification necessary for desired pathway fine-tuning to upgrade products from biomass deconstruction into value-added products. Physics-based modeling approaches such as density functional theory calculations and molecular dynamics simulations have been most impactful in studies aimed at exploring the molecular level details of solvent-biomass interactions, reaction mechanisms occurring in biomass-solvent systems, and the catalytic mechanisms and engineering of enzymes involved in biomass degradation. More recently, with ever increasing amounts of data from, for example, advanced mutli-omics experiments, machine learning approaches have begun to make important contributions in synthetic biology and optimization of metabolic pathways for production of biofuels and chemicals.

Organosolv pretreatment: an in-depth purview of mechanics of the system

“…These systems, when combined with machine learning interfaces have the potential to provide tools for the rapid evaluation of new solvents, deconstruction processes, etc. (Pham et al 2022 ). De Santi et al ( 2021 ) performed a computational study on the acid-assisted lignin β‑ O ‑4 linkage breakdown with stabilization of ethylene glycol via using ReaxFF molecular dynamics, where they setup a realistic scenario of a typical experiment using solute, catalyst, and reagent.…”

Combined Biological and Chemical/Physicochemical Pretreatment Methods of Lignocellulosic Biomass for Bioethanol and Biomethane Energy Production—A Review

“…State-of-theart visualization technologies, such as Raman spectroscopy, atomic force microscopy, and fluorescent labeling, could produce more data to contribute to the understanding of the effect of pretreatment on biomass [82]. Hence, reviews such as this article can help to fill the knowledge gap to develop simulation tools and support synergy between computational and experimental studies with respect to the development of full-scale viable lignocellulosic biomass conversion processes [83].…”

Process systems engineering perspectives on eco-efficient downstream processing of volatile biochemicals from fermentation

“…Lignocellulosic fermentation is a way to turn energy-dense lignocellulosic materials, which would otherwise be wasted, into bioethanol that has the potential as sustainable fuel. Due to the nature of lignocellulosic feedstock, this bioethanol production process does not threaten food production (Pham et al, 2022). Alternatively, gas fermentation can be implemented to avoid complications with biomass pretreatment and increase the amount of carbon that is being utilized.…”