Structure-Activity Relationships of Multifunctional Host Defence Peptides
Bibliographic record
Abstract
Host defence peptides (HDPs) are multi-functional inducers and effectors of host immunity. Through their direct antimicrobial activity HDPs have for been successfully utilized for many years as topical antibiotics and food preservatives. The more recent appreciation of HDP immunomodulatory activities offers additional opportunities for application as systemic antimicrobials, anti-inflammatory agents and vaccine adjuvants. HDPs have demonstrated proof-of-principle success in each of these applications. Optimization of HDPs for these objectives will benefit from a greater comprehension of the structural basis of their various activities. Such an understanding will facilitate rational design and/or selection of peptides with enhanced properties. This is complicated, however, by the diversity of HDP sequences, structures and mechanisms of action. Furthermore, while the ability of HDPs to undergo template-driven formation of bioactive structures enables these small peptides to perform a diverse range of actions it also complicates efforts to understand contributions of particular structural features to specific activities. With recognition of these limitations, but consideration of the emerging importance of this exciting class of molecules, we review the current understanding of the structural basis of select HDP activities as well as present strategies for HDP selection and optimization.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".