Exploring the utility of organo-polyoxometalate hybrids to inhibit SOX transcription factors
Bibliographic record
Abstract
BACKGROUND: SOX transcription factors constitute an attractive target class for intervention with small molecules as they play a prominent role in the field of regenerative biomedicine and cancer biology. However, rationally engineering specific inhibitors that interfere with transcription factor DNA interfaces continues to be a monumental challenge in the field of transcription factor chemical biology. Polyoxometalates (POMs) are inorganic compounds that were previously shown to target the high-mobility group (HMG) of SOX proteins at nanomolar concentrations. In continuation of this work, we carried out an assessment of the selectivity of a panel of newly synthesized organo-polyoxometalate hybrids in targeting different transcription factor families to enable the usage of polyoxometalates as specific SOX transcription factor drugs. RESULTS: The residual DNA-binding activities of 15 different transcription factors were measured after treatment with a panel of diverse polyoxometalates. Polyoxometalates belonging to the Dawson structural class were found to be more potent inhibitors than the Keggin class. Further, organically modified Dawson polyoxometalates were found to be the most potent in inhibiting transcription factor DNA binding activity. The size of the polyoxometalates and its derivitization were found to be the key determinants of their potency. CONCLUSION: Polyoxometalates are highly potent, nanomolar range inhibitors of the DNA binding activity of the Sox-HMG family. However, binding assays involving a limited subset of structurally diverse polyoxometalates revealed a low selectivity profile against different transcription factor families. Further progress in achieving selectivity and deciphering structure-activity relationship of POMs require the identification of POM binding sites on transcription factors using elaborate approaches like X-ray crystallography and multidimensional NMR. In summary, our report reaffirms that transcription factors are challenging molecular architectures and that future polyoxometalate chemistry must consider further modification strategies, to address the substantial challenges involved in achieving target selectivity.
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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".