Evaluation of MMV Pandemic Response Box compounds to identify potent compounds against clinically relevant bacterial and fungal clinical isolates in vitro
Bibliographic record
Abstract
Multidrug resistant bacterial and fungal pathogens are resistant to a number of significant front-line drugs, hence, identification of new inhibitory agents to combat them is crucial. In this study, we aim to evaluate the activity of Pandemic Box compounds from Malaria Medicines Venture (MMV) against A. baumannii and P. aeruginosa bacterial, C.auris, C. albicans and A. niger fungal clinical isolates. Isolates were initially screened with 201 antibacterial and 46 antifungal compounds (10μM) using a microbroth dilution in triplicates to determine MIC. A persister assay was performed for bacterial pathogens. Out of 201 antibacterial compounds, twenty-nine and seven compounds inhibited the growth of A. baumannii and P. aeruginosa at 10 μM, respectively. MMV1580854, MMV1579788, eravacycline and epetraborole inhibited both the bacterial test isolates. In a persister assay, MMV1634390 showed complete bactericidal effect against A. baumannii. With antifungal activity compounds, C.auris responded to15 compounds, Six compounds inhibited C. albicans and one was effective against A. niger at 10μM. The ratio of Minimum Fungicidal Concentration (MFC): Minimum Inhibitory Concentration (MIC) of MMV1782110 was 2 against C. auris. Eberconazole, amorolfine and luliconazole are fungicidal targeting C. albicans at a MFC: MIC ratio of 2. Five compounds from MMV Pandemic Box were found to be inhibiting colistin and ceftazidime resistant A. baumannii clinical isolate, also against colistin and β-lactam resistant P. aeruginosa clinical isolate. MMV1634390 showed complete bactericidal effect against A. baumannii in a persister assay. MMV1782110, Eberconazole, amorolfine and luliconazole exhibited potent anti-fungal activity. Further investigations are warranted to identify the targets and mechanism.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".