Interactive forces between lignin and cellulase as determined by atomic force microscopy
Bibliographic record
Abstract
BACKGROUND: Lignin is a complex polymer which inhibits the enzymatic conversion of cellulose to glucose in lignocellulose biomass for biofuel production. Cellulase enzymes irreversibly bind to lignin, deactivating the enzyme and lowering the overall activity of the hydrolyzing reaction solution. Within this study, atomic force microscopy (AFM) is used to compare the adhesion forces between cellulase and lignin with the forces between cellulase and cellulose, and to study the moiety groups involved in binding of cellulase to lignin. RESULTS: Trichoderma reesei, ATCC 26921, a commercial cellulase system, was immobilized onto silicon wafers and used as a substrate to measure forces involved in cellulase non-productive binding to lignin. Attraction forces between cellulase and lignin, and between cellulase and cellulose were compared using kraft lignin- and hydroxypropyl cellulose-coated tips with the immobilized cellulase substrate. The measured adhesion forces between kraft lignin and cellulase were on average 45% higher than forces between hydroxypropyl cellulose and cellulase. Specialized AFM tips with hydrophobic, -OH, and -COOH chemical characteristics were used with immobilized cellulase to represent hydrophobic, H-bonding, and charge-charge interactions, respectively. Forces between hydrophobic tips and cellulase were on average 43% and 13% higher than forces between cellulase with tips exhibiting OH and COOH groups, respectively. A strong attractive force during the AFM tip approach to the immobilized cellulase was observed with the hydrophobic tip. CONCLUSIONS: This work shows that there is a greater overall attraction between kraft lignin and cellulase than between hydroxypropyl cellulose and cellulase, which may have implications during the enzymatic reaction process. Furthermore, hydrophobic interactions appear to be the dominating attraction force in cellulase binding to lignin, while a number of other interactions may establish the irreversible binding.
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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) | 0.002 | 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".