Design of complement inhibitors that block IgG‐induced C3 activation through its properdin binding site
Bibliographic record
Abstract
Complement dysregulation appears important in the etiology of many autoimmune and inflammatory diseases. IVIG, the C3 inhibitor compstatin and the humanized anti‐C5 antibody Eculizumab modulate complement through direct inhibition of protein activation. In an effort to decipher the mechanisms by which protein‐protein interactions modulate the activation of the complement protein C3 through the classical and alternate cascade, we investigated whether small peptides could interfere with the specific interaction between C3 and properdin. First, we verified that a 34 amino acid peptide, derived from C3, inhibits its interaction with properdin but cannot displace either C3 or properdin from aggregated IgG. Interestingly, a 9‐mer peptide that span within the original 34 amino acids is able to replicate the effect of the 34‐mer toward C3‐properdin interaction. Of utmost interest, further experiments demonstrate that this 9‐mer is also able to inhibit the binding of C3 to IgG. On a molar basis, the active peptide is as powerful as IVIG and an optimized cyclic peptide that inhibits the activation of C3, compstatin. Further analyses demonstrate that the active 9‐mer peptide is able to inhibit complement activation in sensitized red blood cells (SRBC) hemolysis assays. Altogether, these results showed that inhibitory effect of IVIG on in vitro complement activation can be mimicked, at least in part, by a 9‐mer peptide. A quantitative structure‐activity relationship (QSAR) was performed using the minimal active 9‐mer peptide. Linearity and the C‐terminus amino acids were shown to be critical for its activity, and further length reduction of the peptide strongly reduces its activity. We have identified a potent complement inhibitor with potential therapeutic applications in inflammatory and autoimmune diseases.
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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 | 0.001 | 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) | 0.002 | 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 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".