Targeting Mycobacterium tuberculosis and Other Microbial Pathogens Using Improved Synthetic Antibacterial Peptides
Bibliographic record
Abstract
The lack of effective therapies for treating tuberculosis (TB) is a global health problem. While Mycobacterium tuberculosis is notoriously resistant to most available antibiotics, we identified synthetic short cationic antimicrobial peptides that were active at low micromolar concentrations (less than 10 μM). These small peptides (averaging 10 amino acids) had remarkably broad spectra of antimicrobial activities against both bacterial and fungal pathogens and an indication of low cytotoxicity. In addition, their antimicrobial activities displayed various degrees of species specificity that were not related to taxonomy. For example, Candida albicans and Staphylococcus aureus were the best surrogates to predict peptide activity against M. tuberculosis, while Mycobacterium smegmatis was a poor surrogate. Principle component analysis of activity spectrum profiles identified unique features associated with activity against M. tuberculosis that reflect their distinctive amino acid composition; active peptides were more hydrophobic and cationic, reflecting increased tryptophan with compensating decreases in valine and other uncharged amino acids and increased lysine. These studies provide foundations for development of cationic antimicrobial peptides as potential new therapeutic agents for TB treatment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 teacher head, 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".