Comparison of the Interaction Modes Between Cellulase and Bovine Serum Albumin /Lignosulfonate /Polyethylene Glycol in Promoting Lignocellulose Saccharification
Bibliographic record
Abstract
Abstract Background: Bovine serum albumin (BSA), polyethylene glycol (PEG) and lignosulfonate (LS) have been extensively employed as synergistic agents in lignocellulose saccharification, albeit it has not been fully understood how they interact with enzymes from the perspectives of molecular interactions. Herein, we attempted to unveil the promotion mechanisms of BSA, PEG and LS for lignocellulose saccharification from the perspective of their respective interaction with cellulase using Quartz Crystal Microbalance with Dissipation monitoring (QCM-D), Surface Plasmon Resonance (SPR), and Small Angle X-ray Scattering (SAXS) to investigate their respective interaction and the complex formation. In the meanwhile, we compared the effects of adding these additives into the enzymatic hydrolysis of pure cellulose (Avicel) and green liquor-pretreated lignocellulose (GL).Results: The results showed that BSA and LS could bind to cellulase to form complexes, whereas PEG did not. However, PEG had a high affinity to lignin or lignin derivatives. In term for Avicel and GL substrates, the results showed that BSA and PEG promoted the enzymatic hydrolysis of both substrates, while LS had a promoting effect for GL only and inhibited some extent for Avicel. Conclusions: This study showed that synergistic agents of LS, BSA, and PEG have different interaction modes with cellulase. BSA and LS form complexes with cellulase and the formed complexes prevent from nonproductive binding by residue lignin; whereas PEG prevents from nonproductive binding by forming a thin layer on residue lignin which actually serve as steric hindrance. This investigation will help us to understand the sophisticated interactions among the components in the complicated enzymatic system, especially the interactions between enzymes and synergistic agents. It will be helpful in the design and utilization of synergistic additives in the lignocellulose biorefinery process as well.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".