High Affinity Inhibitors of the Macrophage Infectivity Potentiator Protein from <i>Trypanosoma cruzi</i>, <i>Burkholderia pseudomallei</i>, and <i>Legionella pneumophila</i>─A Comparison
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Since Chagas disease, melioidosis, and Legionnaires’ disease are all potentially life-threatening infections, there is an urgent need for new treatment strategies. All causative agents, Trypanosoma cruzi, Burkholderia pseudomallei, and Legionella pneumophila, express a virulence factor, the macrophage infectivity potentiator (MIP) protein, emerging as a promising new therapeutic target. Inhibition of MIP proteins having a peptidyl-prolyl isomerase activity leads to reduced viability, proliferation, and cell invasion. The affinity of a series of pipecolic acid-type MIP inhibitors was evaluated against all MIPs using a fluorescence polarization assay. The analysis of structure–activity relationships led to highly active inhibitors of MIPs of all pathogens, characterized by a one-digit nanomolar affinity for the MIPs and a very effective inhibition of their peptidyl-prolyl isomerase activity. Docking studies, molecular dynamics simulations, and quantum mechanical calculations suggest an extended σ-hole of the meta -halogenated phenyl sulfonamide to be responsible for the high affinity.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".