From Naturally-Sourced Protease Inhibitors to New Treatments for Fungal Infections
Bibliographic record
Abstract
Proteases are involved in a broad range of physiological processes, including host invasion by fungal pathogens, and enzymatic inhibition is a key molecular mechanism controlling proteolytic activity. Importantly, inhibitors from natural or synthetic sources have demonstrated applications in biochemistry, biotechnology, and biomedicine. However, the need to discover new reservoirs of these inhibitory molecules with improved efficacy and target range has been underscored by recent protease characterization related to infection and antimicrobial resistance. In this regard, naturally-sourced inhibitors show promise for application in diverse biological systems due to high stability at physiological conditions and low cytotoxicity. Moreover, natural sources (e.g., plants, invertebrates, and microbes) provide a large reservoir of undiscovered and/or uncharacterized bioactive molecules involved in host defense against predators and pathogens. In this Review, we highlight discoveries of protease inhibitors from environmental sources, propose new opportunities for assessment of antifungal activity, and discuss novel applications to combat biomedically-relevant fungal diseases with in vivo and clinical purpose.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".