Defining unique structural features in the MAFA and MAFB transcription factors that control <i>Insulin</i> gene activity
Bibliographic record
Abstract
ABSTRACT MAFA and MAFB are related basic-leucine-zipper domain containing transcription factors which have important overlapping and distinct regulatory roles in a variety of cellular contexts, including hormone production in pancreatic islet α and β cells. Here we first examined how mutating conserved MAF protein-DNA contacts obtained from X-ray crystal structure analysis impacted their DNA-binding and Insulin enhancer-driven activity. While most of these interactions were essential and their disruption severely compromised activity, we identified that regions outside of the contact areas also contributed to activity. AlphaFold 2, an artificial intelligence-based structural prediction program, was next used to determine if there were also differences in the three-dimensional organization of the non-DNA binding/dimerization sequences of MAFA and MAFB. This analysis was conducted on the wildtype (WT) proteins as well as the pathogenic MAFA Ser64Phe and MAFB Ser70Ala trans -activation domain mutants, with differences revealed between MAFA WT and MAFB WT as well as between MAFA Ser64Phe and MAFA WT , but not between MAFB Ser70Ala and MAFB WT . Moreover, dissimilarities between these proteins were also observed in their ability to cooperatively stimulate Insulin enhancer-driven activity in the presence of other islet-enriched transcription factors. Analysis of MAFA and MAFB chimeras disclosed that these properties were greatly influenced by unique C-terminal region structural differences predicted by AlphaFold 2. Importantly, these results have revealed features of these closely related proteins that are functionally significant in islet biology.
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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".