From Metabolism to Mutation: The Multifaceted Roles of Deaminases in Biological Systems
Bibliographic record
Abstract
Deaminases are versatile enzymes present across all domains of life, playing pivotal roles in metabolism, cellular and organ development, heme and vitamin biosynthesis, toxin modulation, antibiotic degradation, the modification of nucleobases, and the mutation of RNA and DNA. This review explores the structural and functional diversity of deaminases, highlighting their mechanisms and evolutionary adaptations. Deaminases catalyze the removal of amine groups, typically using metal cations and proton shuttles to facilitate hydroxyl group incorporation, with some reactions employing pyridoxal 5'-phosphate (PLP) as a cofactor. The review categorizes deaminases based on their substrates, including porphobilinogen, amino sugars, amino acids, and nucleobases. Particular emphasis is placed on nucleobase deaminases due to their roles in RNA/DNA editing and mutagenesis which have significant implications in immune response, cancer progression, and viral defense mechanisms. Structural insights reveal the diverse evolutionary pathways of these enzymes, from simple single-domain forms to complex multi-domain configurations that enable processive deamination of polynucleotides. Through a comprehensive analysis of deaminase families—PBGD, sugar deaminases, amino acid deaminases, and nucleobase deaminases—this review underscores their biological significance and potential applications in agriculture, medicine, and biotechnology, providing a foundational understanding for future research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".