Identification of the high affinity binding site in the Streptococcus intermedius toxin intermedilysin for its membrane receptor, the human complement regulator CD59
Bibliographic record
Abstract
The unique species specificity of the bacterial cytolysin intermedilysin is explained by its requirement for the human complement regulator CD59 as the primary receptor. Binding studies using individual domains of intermedilysin mapped the CD59-binding site to domain 4 and swap mutants between human and rabbit (non-intermedilysin-binding) CD59 implicated a short sequence (residues 42-59) in human CD59 in binding intermedilysin. We set out to map more closely the CD59 binding site in intermedilysin. We first looked for regions of homology between domain 4 in intermedilysin and the terminal complement components that bind CD59, C8 and C9. A nine amino acid sequence immediately adjacent the undecapeptide segment in intermedilysin domain 4 matched (5 of 9 identical, 3 of 9 conserved) a sequence in C9. A peptide containing this sequence caused dose-dependent inhibition of intermedilysin-mediated lysis of human erythrocytes and rendered erythrocytes more susceptible to complement lysis. Surface plasmon resonance analysis of intermedilysin binding to immobilized CD59 revealed saturable fast-on, fast-off binding and a calculated affinity of 4.9 nM. Substitution of three residues from the putative binding site caused a 5-fold reduction in lytic potency of intermedilysin and reduced affinity for immobilized CD59 by 2.5-fold. The demonstration that a peptide modeled on the CD59-binding site inhibits intermedilysin-mediated haemolysis leads us to suggest that such peptides might be useful in treating infections caused by intermedilysin-producing bacteria.
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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 | 0.001 |
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".