A Potent <scp>d</scp>-Protein Antagonist of VEGF-A is Nonimmunogenic, Metabolically Stable, and Longer-Circulating <i>in Vivo</i>
Bibliographic record
Abstract
Polypeptides composed entirely of d-amino acids and the achiral amino acid glycine (d-proteins) inherently have in vivo properties that are proposed to be near-optimal for a large molecule therapeutic agent. Specifically, d-proteins are resistant to degradation by proteases and are anticipated to be nonimmunogenic. Furthermore, d-proteins are manufactured chemically and can be engineered to have other desirable properties, such as improved stability, affinity, and pharmacokinetics. Thus, a well-designed d-protein therapeutic would likely have significant advantages over l-protein drugs. Toward the goal of developing d-protein therapeutics, we previously generated RFX001.D, a d-protein antagonist of natural vascular endothelial growth factor A (VEGF-A) that inhibited binding to its receptor. However, RFX001.D is unstable at physiological temperatures (Tm = 33 °C). Here, we describe RFX037.D, a variant of RFX001.D with extreme thermal stability (Tm > 95 °C), high affinity for VEGF-A (Kd = 6 nM), and improved receptor blocking. Comparison of the two enantiomeric forms of RFX037 revealed that the d-protein is more stable in mouse, monkey, and human plasma and has a longer half-life in vivo in mice. Significantly, RFX037.D was nonimmunogenic in mice, whereas the l-enantiomer generated a strong immune response. These results confirm the potential utility of synthetic d-proteins as alternatives to therapeutic antibodies.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".