Organocatalytic Switches of DNA Glycosylase OGG1 Catalyze a Highly Efficient AP‐Lyase Function
Bibliographic record
Abstract
Abstract 8‐oxoGuanine DNA glycosylase 1 (OGG1) is the first known target of organocatalytic switches (ORCAs), which rewrite the biochemical function of the enzyme through redirection of its preferred substrate from 8‐oxoG to AP sites. Previously, different ORCA chemotypes were shown to enhance the operational pH window for OGG1, possibly through direct involvement in proton transfer events during DNA strand cleavage. Accordingly, compound pK a is a crucial and necessary consideration for the identification and application of future OGG1 ORCAs. Here, we identify a minimal structure of organocatalytic switches–4‐anilino pyridines and 6‐anilino pyrimidines–which are dimethyl‐amino‐pyridine (DMAP)‐type Brønsted bases binding the active site of OGG1. Systematic interrogation of compound basicity through modulation of electron‐withdrawing (EWG) and electron‐donating (EDG) substituents reveals that a pK a less or equal to the assay pH is a viable parameter for prediction of compound activity. The lead structure (AC 50 13 nM, pK a 7.0) was then identified as a potent scaffold from a screen in a patient‐derived 3D model of metabolic dysfunction‐associated steatohepatitis (MASH), where it reduced hepatic fibrosis by 35%. Collectively, these findings deepen the knowledge of this novel modulator class, with important implications for future enzyme targets and probe development.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".