Insights into Active Site Cysteine Residues in Mycobacterium tuberculosis Enzymes: Potential Targets for Anti-Tuberculosis Intervention
Bibliographic record
Abstract
Cysteine, a semi-essential amino acid, is found in the active site of a number of vital enzymes of the bacterium Mycobacterium tuberculosis (Mtb) and in particular those that relate to its survival, adaptability and pathogenicity. Mtb is the causative agent of tuberculosis, an infectious disease that affects millions of people globally. Common anti-tuberculosis targets are focused on immobilizing a vital cysteine amino acid residue in enzymes that plays critical roles in redox and non-redox catalysis, the modulation of the protein, enzyme activity, protein structure and folding, metal coordination, and posttranslational modifications of newly synthesized proteins. This review examines five Mtb enzymes that contain an active site cysteine residue and are considered as key targets for anti-tuberculosis drugs, namely alkyl hydroperoxide reductase (AhpC), dihydrolipoamide dehydrogenase (Lpd), aldehyde dehydrogenase (ALDH), methionine aminopeptidase (MetAP) and cytochromes P450. AhpC and Lpd protect Mtb against oxidative and nitrosative stress, whereas AhpC neutralizes peroxide/peroxynitrite substrates with two active site cysteine residues. Mtb ALDH detoxifies aldehydes, using a nucleophilic active site cysteine to form an oxyanion thiohemiacetal intermediate, whereas MtMetAP’s active site cysteine is essential for substrate recognition. The P450s metabolize various endogenous and exogenous compounds. Targeting these critical active site cysteine residues could disrupt enzyme functions, presenting a promising avenue for developing anti-mycobacterial agents.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".