Insights into the cellular function and mechanism of action of quinone reductase 2 (NQO2)
Bibliographic record
Abstract
Quinone reductase 2 (NQO2) is a FAD-linked enzyme that cannot use the common reducing cofactors, NADH and NADPH, for efficient catalysis. This is unusual for an oxidoreductase, particularly since it is a member of a large family of enzymes that all use NAD(P)H efficiently to catalyse the two-electron reduction in quinones and other electrophiles. The inability of NQO2 to use NAD(P)H efficiently raises questions about its cellular function: it remains unclear whether the main cellular role of NQO2 is the catalytic reduction in quinones or whether it is a pseudo-enzyme with other roles such as cell signalling. Intriguingly, NQO2 has been identified as an off-target interactor with over 30 kinase inhibitors and other drugs and natural products. The interaction between NQO2 and kinase-targeted drugs is particularly intriguing because it suggests that NQO2 may be contributing to the cellular effects of these drugs. In this review, we will discuss the enzymatic properties of NQO2, its structure and complexes with various drugs and small molecules, potential cellular roles, and some of the enigmatic findings that make this molecule so interesting and worthy of further investigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".