Method to generate highly stable D-amino acid analogs of bioactive helical peptides using a mirror image of the entire PDB
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Significance Using D-amino acids as the building blocks for bioactive peptides can dramatically increase their potency. However, simply swapping regular levorotary amino acids for dextrorotary (D)-amino acids alters the peptide surface topology and function is lost. Current methods to overcome this are not generally applicable and exclude the majority of therapeutic targets. By creating a mirror image of all 111,867 protein structures in the Protein Data Bank (PDB), we convert this repository into a D-peptide database with 2.8 million D-peptide structures. This D-PDB can be searched to find therapeutically active topologies, demonstrated here by the discovery of D-peptide GLP1R and PTH1R agonists. Evaluation of D-PDB coverage suggests that it holds candidates for most therapeutic targets and, thus, potentially contains hundreds of potent drug leads.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it