Development of Peptide Displacement Assays to Screen for Antagonists of DDB1 Interactions
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The DNA damage binding protein 1 (DDB1) is an essential component of protein complexes involved in DNA damage repair and the ubiquitin-proteasome system (UPS) for protein degradation. As an adaptor protein specific to Cullin-RING E3 ligases, DDB1 binds different receptors that poise protein substrates for ubiquitination and subsequent degradation by the 26S proteasome. Examples of DDB1-binding protein receptors are Cereblon (CRBN) and the WD-repeat containing D DB1- and C UL4- a ssociated f actors (DCAFs). Cognate substrates of CRBN and DCAFs are involved in cancer-related cellular processes or are mimicked by viruses to reprogram E3 ligases for the ubiquitination of antiviral host factors. Thus, disrupting interactions of DDB1 with receptor proteins might be an effective strategy for anticancer and antiviral drug discovery. Here, we developed fluorescence polarization (FP)-based peptide displacement assays that utilize full-length DDB1 and fluorescein isothiocyanate (FITC)-labeled peptide probes derived from the specific binding motifs of DDB1 interactors. A general FP-based assay condition applicable to diverse peptide probes was determined and optimized. Mutagenesis and biophysical analyses were then employed to identify the most suitable peptide probe. The FITC-DCAF15 L49A peptide binds DDB1 with a dissociation constant of 68 nM and can be displaced competitively by unlabeled peptides at sub-μM to low nM concentrations. These peptide displacement assays can be used to screen small molecule libraries to identify novel modulators that could specifically antagonize DDB1 interactions toward development of antiviral and cancer therapeutics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".