Retinol dehydrogenases: Membrane-bound enzymes for the visual function
Bibliographic record
Abstract
Retinoid metabolism is important for many physiological functions, such as differenciation, growth, and vision. In the visual context, after the absorption of light in rod photoreceptors by the visual pigment rhodopsin, 11-cis retinal is isomerized to all-trans retinal. This retinoid subsequently undergoes a series of modifications during the visual cycle through a cascade of reactions occurring in photoreceptors and in the retinal pigment epithelium. Retinol dehydrogenases (RDHs) are enzymes responsible for crucial steps of this visual cycle. They belong to a large family of proteins designated as short-chain dehydrogenases/reductases. The structure of these RDHs has been predicted using modern bioinformatics tools, which allowed to propose models with similar structures including a common Rossman fold. These enzymes undergo oxidoreduction reactions, whose direction is dictated by the preference and concentration of their individual cofactor (NAD(H)/NADP(H)). This review presents the current state of knowledge on functional and structural features of RDHs involved in the visual cycle as well as knockout models. RDHs are described as integral or peripheral enzymes. A topology model of the membrane binding of these RDHs via their N- and (or) C-terminal domain has been proposed on the basis of their individual properties. Membrane binding is a crucial issue for these enzymes because of the high hydrophobicity of their retinoid substrates.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".