Structural and functional properties of pectin and lignin–carbohydrate complexes de-esterases: a review
Bibliographic record
Abstract
Biological conversion of plant biomass into commercially valuable products is one of the highly studied subjects in the last two decades. Studies were continuously being conducted to understand and develop efficient enzymes for the breakdown and conversion of plant cell-wall components into valuable commercial products. Naturally, plant cell-wall components are differentially esterified to protect from the invading microorganisms. However, during the process of evolution, microorganisms have developed special set of enzymes to de-esterify the plant cell-wall components. Among the carbohydrate-active enzymes (CAZy), carbohydrate esterases stand first during the process of enzymatic conversion of plant biomass, as these enzymes de-esterify the plant biomass and make it accessible for the hydrolytic enzymes such as cellulases, hemicellulases, ligninolytic and pectinases. In this article, we have extensively discussed about the structural and functional properties of pectin methyl esterases, feruloyl, cinnamoyl and glucuronoyl esterases which are required for the de-esterification of pectin and lignin–carbohydrate complexes. Pectin esterases are classified among CE8, CE12, CE13 and CE15 carbohydrate esterase class of CAZy database. Whereas, lignin–carbohydrate complex de-esterifying enzymes are classified among CE1 (feruloyl esterase) and CE15 (glucuronoyl esterase) classes. Understanding the structural and functional abilities of pectin and lignin–carbohydrate esterases will significantly aid in developing efficient class of de-esterases for reducing the recalcitrant nature of plant biomass. These efficient de-esterases will have various applications including pretreatment of plant biomass, food, beverage, pulp and paper, textile, pharmaceutical and biofuel industries.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".