Inhibition of <i>Mycobacterium tuberculosis</i>, <i>Mycobacterium bovis</i>, and <i>Mycobacterium </i><i>avium</i> by Novel Dideoxy Nucleosides
Bibliographic record
Abstract
The prevalence of tuberculosis (TB) and mutidrug-resistant tuberculosis (MDR-TB) has been increasing, leading to serious infections, high mortality, and a global health threat. Here, we report the identification of a novel class of dideoxy nucleosides as potent and selective inhibitors of Mycobacterium bovis, Mycobacterium tuberculosis, and drug-resistant Mycobacterium tuberculosis. A series of 5-acetylenic derivatives of 2',3'-dideoxyuridine (3-8) and 3'-fluoro-2',3'-dideoxyuridine (22-27) were synthesized and tested for their antimycobacterial activity against M. bovis, M. tuberculosis, and M. avium. 2',3'-Dideoxyuridine possessing 5-decynyl, 5-dodecynyl, 5-tridecynyl, and 5-tetradecynyl substituents (4-7) exhibited the highest antimycobacterial activity against all three mycobacteria. In contrast, in the 3'-fluoro-2',3'-dideoxyuridine series, a 5-tetradecynyl analogue (26) displayed the most potent activity against these mycobacteria. Among other derivatives, 5-bromo-2',3'-dideoxycytidine (11), 5-methyl-2',3'-dideoxycytidine (12), and 5-chloro-4-thio-2',3'-dideoxyuridine (19) exhibited modest inhibition of M. bovis and M. tuberculosis. In the series of dideoxy derivatives of adenosine, guanosine, and purines, 2-amino-6-mercaptoethyl-9-(2,3-dideoxy-beta-d-glyceropentofuranosyl)purine (32) and 2-amino-4-fluoro-7-(2,3-dideoxy-beta-d-glyceropentofuranosyl)pyrrolo[2,3-d]pyrimidine (35) were the most efficacious against M. bovis and M. tuberculosis, and M. avium, respectively.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".