Host Defence (Antimicrobial) Peptides and Proteins
Bibliographic record
Abstract
Abstract Host defence (antimicrobial) peptides are small cationic peptides that contain several hydrophobic amino acids. Such peptides typically form amphipathic structures in membrane‐mimicking environments, which contribute to peptide activity on essential membrane‐dependent processes, membrane permeabilisation and/or cell penetration. Host defence peptides (HDPs) have a variety of biological properties, including profound immune‐modulating properties and direct antibacterial, antiviral, antifungal, antiparasitic and anticancer activities. Thus, HDPs are important effectors of the immune system; however, the effector functions of these peptides are often heavily dependent on their microenvironment. The direct antibacterial properties of many peptides are eliminated in the presence of physiologically relevant concentrations of cations and polyanions, although the immune‐modulating properties of these peptides persist under these conditions even in the presence of serum. The immune‐modulating properties are anti‐infective and include chemokine induction and host cell recruitment/differentiation, antiinflammatory activity, promotion of effective adaptive immunity and wound healing activity. Using human peptides as examples, the biological properties of HDPs are discussed herein in an attempt to expose their potential as templates for novel therapeutic agents. Key Concepts: The direct antimicrobial properties of small cationic peptides are often eliminated in the presence of physiologically relevant concentrations of serum and salt; thus they are more accurately described as host defence peptides. The immunomodulatory properties of host defence peptides are complex, have been confirmed in vivo , and contribute to anti‐infective immunity. Humans express several defensins and one cathelicidin (hCAP‐18/LL‐37). Human defensins and cathelicidins are produced by many cell types and have many biological properties, including the ability to destroy pathogens and alter immune responses. Host defence peptides can be modified to improve their biological activities.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".