Investigating the Effects of Hydrophobicity and Charge on the Therapeutic Ability of the Antimicrobial Histatin 8 Peptide for Potential Use in Oral Applications
Bibliographic record
Abstract
Advances in technology allow for the construction of synthetic antibiotics, which includes the development of de novo antimicrobial peptides (AMPs). The contents of AMPs including amino acids, chain length, hydrophobicity, ring structure/rigidity, terminus and charge when modified can alter the antimicrobial properties. A special family of peptides called histatins is naturally excreted by oral glands as an immune response, and previous research shows their potential for treating thrush. Histatin 8 is known to have antimicrobial activity against yeast strains and the goal of this study was to synthesize histatin 8 and two novel derivatives (delt 1 and delt 4) that fall at extremes of each other with regard to charge and hydrophobicity in order to investigate the properties that could optimize antimicrobial properties. The derivatives were characterized using various chemical and biological assays to investigate the effects of charge and hydrophobicity on bioactivity. Compared to histatin 8, delt 4’s minimum inhibitory concentration (MIC) was decreased more than tenfold against Candida tropicalis indicating increased antimicrobial activity. Re-inoculation confirmed fungicidal properties.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".