Fragment-Based Design of Symmetrical Bis-benzimidazoles as Selective Inhibitors of the Trimethoprim-Resistant, Type II R67 Dihydrofolate Reductase
Bibliographic record
Abstract
The continuously increasing use of trimethoprim as a common antibiotic for medical use and for prophylactic application in terrestrial and aquatic animal farming has increased its prevalence in the environment. This has been accompanied by increased drug resistance, generally in the form of alterations in the drug target, dihydrofolate reductase (DHFR). The most highly resistant variants of DHFR are known as type II DHFR, among which R67 DHFR is the most broadly studied variant. We report the first attempt at designing specific inhibitors to this emerging drug target by fragment-based design. The detection of inhibition in R67 DHFR was accompanied by parallel monitoring of the human DHFR, as an assessment of compound selectivity. By those means, small aromatic molecules of 150-250 g/mol (fragments) inhibiting R67 DHFR selectively in the low millimolar range were identified. More complex, symmetrical bis-benzimidazoles and a bis-carboxyphenyl were then assayed as fragment-based leads, which procured selective inhibition of the target in the low micromolar range (K(i) = 2-4 μM). The putative mode of inhibition is discussed according to molecular modeling supported by in vitro tests.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".