Characterisation of Potential Antimicrobial Targets for Tuberculosis. 2. Branched-Chain Amino Acid Aminotransferase and Methionine Regeneration in Mycobacterium Tuberculosis
Bibliographic record
Abstract
Tuberculosis remains an important problem for the Canadian Forces in many of its overseas deployments. With the spread of drug-resistant strains of Mycohactenum tubercuThsis, there is an increased need to characterise novel drug targets in the organism. The final step of methionine recycling from methylthioadenosine has been examined in M tuberculosis, and has been found to be catalysed by a branched-chain amino acid aminotransferase. The enzyme was found to be a member of the aminotransferase lila subfamily, and closely related to the corresponding aminotransferase in Bacillus subtilis, but not to that found in B. anthracis or B. cereus (Berger et al., Journal of Bacteriology, 185, p. 2418-2431, 2003). The amino donor preference for the formation of methionine from ketomethiobutyrate was isoleucine, leucine, valine, glutamate, and phenylalanine. The en%me catalysed branched-chain amino acid and ketomethiobutyrate transamination with a Km of 1.77 - 7.44 mM and a Vmax of 2.17 - 5.70 %mol/min/mg protein, and transamination of ketoglutarate with a Km of 5.79 - 6.95 mM and a Vmax of 11.82 - 14.35 %mol/min/mg protein. Aminooxy compounds were examined as potential enzyme inhibitors, with O-benzylhydroxylamine, o-t- butylhydroxylamine, carboxymethoxylamine, and 0-allylhydroxylamine yielding mixed-type inhibition with Ki values of 8.20 - 21.61 %M. These same compounds were examined as antimycobacterial agents in a M inarinum model and were found to completely prevent cell growth. 0-allylhydroxylamine was the most effective growth inhibitor with an MIC of 78 tjM and an 1C50 of 8.49 %M.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".