Alternative oxidase: what information can protein sequence comparisons give us?
Bibliographic record
Abstract
The finding that alternative oxidase (AOX) is present in most kingdoms of life has resulted in a large number of AOX sequences that are available for analyses. Multiple sequence alignments of AOX proteins from evolutionarily divergent organisms represent a valuable tool and can be used to identify amino acids and domains that may play a role in catalysis, membrane association and post-translational regulation, especially when these data are coupled with the structural model for the enzyme. I validate the use of this approach by demonstrating that it detects the conserved glutamate and histidine residues in AOX that initially led to its identification as a di-iron carboxylate protein and the generation of a structural model for the protein. A comparative analysis using a larger dataset identified 35 additional amino acids that are conserved in all AOXs examined, 30 of which have not been investigated to date. I hypothesize that these residues will be involved in the quinol terminal oxidase activity or membrane association of AOX. Major differences in AOX protein sequences between kingdoms are revealed, and it is hypothesized that two angiosperm-specific domains may be responsible for the non-covalent dimerization of AOX, whereas two indels in the aplastidic AOXs may play a role in their post-translational regulation. A scheme for predicting whether a particular AOX protein will be recognized by the alternative oxidase monoclonal antibody generated against the AOX of Sauromatum guttatum (Voodoo lily) is presented. The number of functional sites in AOX is greater than expected, and determining the structure of AOX will prove extremely valuable to 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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.015 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".