In Vitro Identification of Histatin 5 Salivary Complexes
Bibliographic record
Abstract
With recent progress in the analysis of the salivary proteome, the number of salivary proteins identified has increased dramatically. However, the physiological functions of many of the newly discovered proteins remain unclear. Closely related to the study of a protein's function is the identification of its interaction partners. Although in saliva some proteins may act primarily as single monomeric units, a significant percentage of all salivary proteins, if not the majority, appear to act in complexes with partners to execute their diverse functions. Coimmunoprecipitation (Co-IP) and pull-down assays were used to identify the heterotypic complexes between histatin 5, a potent natural antifungal protein, and other salivary proteins in saliva. Classical protein-protein interaction methods in combination with high-throughput mass spectrometric techniques were carried out. Co-IP using protein G magnetic Sepharose TM beads suspension was able to capture salivary complexes formed between histatin 5 and its salivary protein partners. Pull-down assay was used to confirm histatin 5 protein partners. A total of 52 different proteins were identified to interact with histatin 5. The present study used proteomic approaches in conjunction with classical biochemical methods to investigate protein-protein interaction in human saliva. Our study demonstrated that when histatin 5 is complexed with salivary amylase, one of the 52 proteins identified as a histatin 5 partner, the antifungal activity of histatin 5 is reduced. We expected that our proteomic approach could serve as a basis for future studies on the mechanism and structural-characterization of those salivary protein interactions to understand their clinical significance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".