ArticleBiotechnology for biofuels2012
A coarse-grained model for synergistic action of multiple enzymes on cellulose.
Article in Biotechnology for biofuels, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 46 citations in OpenAlex.
- Upcycling Vegetable Waste Into Functional Food Ingredients via Synergistic Microbial Engineering and Artificial Intelligence.Comprehensive reviews in food science and food safety · 2026Review
- Stochastic model highlights the impact of crystallinity on saccharification dynamics depending on plant chemotype and pre-treatment.PloS one · 2025Article
- A detailed sensitivity analysis identifies the key factors influencing the enzymatic saccharification of lignocellulosic biomass.Computational and structural biotechnology journal · 2024Article
- PREDIG: Web application to model and predict the enzymatic saccharification of plant cell wall.Computational and structural biotechnology journal · 2023Article
- Building an extensible cell wall.Plant physiology · 2022Article
- Stochastic model of lignocellulosic material saccharification.PLoS computational biology · 2021Article
- Co-expression of cellulase and xylanase genes inBioengineered · 2019Article
- Cellular automata modeling depicts degradation of cellulosic material by a cellulase system with single-molecule resolution.Biotechnology for biofuels · 2016Article
- Systems-level modeling with molecular resolution elucidates the rate-limiting mechanisms of cellulose decomposition by cellobiohydrolases.The Journal of biological chemistry · 2013Article
- Stochastic molecular model of enzymatic hydrolysis of cellulose for ethanol production.Biotechnology for biofuels · 2013Article
- Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.Wiley interdisciplinary reviews. Systems biology and medicineReview
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDegradation of cellulose to glucose requires the cooperative action of three classes of enzymes, collectively known as cellulases. Endoglucanases randomly bind to cellulose surfaces and generate new chain ends by hydrolyzing β-1,4-D-glycosidic bonds. Exoglucanases bind to free chain ends and hydrolyze glycosidic bonds in a processive manner releasing cellobiose units. Then, β-glucosidases hydrolyze soluble cellobiose to glucose. Optimal synergistic action of these enzymes is essential for efficient digestion of cellulose. Experiments show that as hydrolysis proceeds and the cellulose substrate becomes more heterogeneous, the overall degradation slows down. As catalysis occurs on the surface of crystalline cellulose, several factors affect the overall hydrolysis. Therefore, spatial models of cellulose degradation must capture effects such as enzyme crowding and surface heterogeneity, which have been shown to lead to a reduction in hydrolysis rates.
resultsWe present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level. This functional model accounts for the mobility and action of a single cellulase enzyme as well as the synergy of multiple endo- and exo-cellulases on a cellulose surface. The quantitative description of cellulose degradation is calculated on a spatial model by including free and bound states of both endo- and exo-cellulases with explicit reactive surface terms (e.g., hydrogen bond breaking, covalent bond cleavages) and corresponding reaction rates. The dynamical evolution of the system is simulated by including physical interactions between cellulases and cellulose.
conclusionsOur coarse-grained model reproduces the qualitative behavior of endoglucanases and exoglucanases by accounting for the spatial heterogeneity of the cellulose surface as well as other spatial factors such as enzyme crowding. Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails. This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.