<i>In vitro</i>activity (MICs and rate of kill) of AFN-1252, a novel FabI inhibitor, in the presence of serum and in combination with other antibiotics
Bibliographic record
Abstract
AFN-1252 is a novel inhibitor of FabI, an essential enzyme in fatty acid biosynthesis in Staphylococcus spp. AFN-1252 exhibits typical MIC(90) values of ≤0·015 μg/ml against diverse clinical isolates of S. aureus, oral absorption, long elimination half-live and efficacy in animal models. We now report high binding (∼95%) to serum proteins of mouse, rat, dog and humans, associated with an eight-fold increase in minimal inhibitory concentration (MIC) and which may be responsible for the long elimination half-lives on pharmacokinetic studies. Unlike daptomycin, AFN-1252 activity is not reduced in the presence of lung surfactant. AFN-1252 exhibits a short post-antibiotic effect of 1·1 hours against methicillin-susceptible S. aureus (MSSA) and methicillin-resistant S. aureus (MRSA) following a 4-hour exposure period. The AFN-1252 unique spectrum of activity is not compromised by interactions with major antibiotic classes, but demonstrates synergy with low concentrations of gentamicin against MSSA and MRSA. These studies support the continued investigation of AFN-1252 as a targeted therapeutic for staphylococcal infections.
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 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 | 0.000 | 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 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".