Global Protein Interaction Network for <i>Trypanosoma cruzi</i>
Bibliographic record
Abstract
Trypanosoma cruzi, the causative agent of Chagas disease, poses a significant health challenge due to limited therapeutic options and an incomplete understanding of its biology. Approximately half of the genome encodes hypothetical proteins with unknown functions, underscoring the need for systematic functional annotation. Protein–protein interactions (PPIs) underpin essential cellular processes, yet no large-scale PPI map has been developed for T. cruzi ─a critical gap that impedes both functional annotation of its proteome and drug discovery. This study presents the first comprehensive PPI network for T. cruzi, constructed using quantitative mass spectrometry-based cofractionation data. The network includes 1319 proteins and more than 16,000 predicted interactions, with 47% of the proteins classified as hypothetical, consistent with the 49% hypothetical annotation rate in the proteome. Their placement within functionally enriched network modules provides unprecedented insights into their potential biological roles. Network analysis revealed densely interconnected cores enriched with essential cellular functions. This PPI network exhibits small-world properties, with conserved proteins showing higher connectivity, reinforcing their central roles in the parasite’s biology. This resource, publicly available at https://2025.trypsnetdb.org/, offers a powerful platform for exploring T. cruzi biology and prioritizing novel therapeutic targets, revealing central hubs of protein organization, resolving ribosomal and proteasomal complexes, and enabling functional predictions for numerous hypothetical proteins through integrative structural modeling.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".