The spatial separation of basic amino acids is similar in RHAMM and hyaluronan binding peptide P15‐1 despite different sequences and conformations
Bibliographic record
Abstract
Peptides that increase pro-reparative responses to injury and disease by modulating the functional organization of hyaluronan (HA) with its cell surface binding proteins (e.g., soluble receptor for hyaluronan-mediated motility [RHAMM] and integral membrane CD44) have potential therapeutic value. The binding of RHAMM to HA is an attractive target, since RHAMM is normally absent or expressed at low levels in homeostatic conditions, but its expression is significantly elevated in the extracellular matrix during tissue stress, response-to-injury, and in cancers and inflammation-based diseases. The HA-binding site in RHAMM contains two closely spaced sequences of clustered basic amino acids, in an alpha-helical conformation. In the present communication, we test whether an alpha-helical conformation is required for effective peptide binding to HA, and competitive disruption of HA-RHAMM interaction. The HA-binding RHAMM-competitive peptide P15-1, identified using the unbiased approach of phage display, was examined using circular dichroism spectroscopy and the conformation-predictive AI-based AlphaFold2 algorithm. Unlike the HA-binding site in RHAMM, peptide P15-1 was found to adopt irregular conformations in solution rather than alpha helices. Instead, our structural analysis suggests that the primary determinant of peptide-HA binding is associated with a specific clustering and spacing pattern of basic amino acids, allowing favorable electrostatic interaction with carboxylate groups on HA.
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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 | 0.000 |
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 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".