Proteome-wide comparison of tertiary protein structures reveal extensive molecular mimicry in <i>Plasmodium</i> -human interactions
Bibliographic record
Abstract
Abstract Molecular mimicry is a strategy used by parasites to escape the host immune system and successfully transmit to a new host. To date, high-throughput examples of molecular mimicry have been limited to comparing protein sequences. However, with advances in the prediction of tertiary structural models, led by Deepmind’s AlphaFold, it is now possible to compare the tertiary structures of thousands of proteins from parasites and their hosts, to identify more subtle mimics. Here, we present the first proteome-level search for tertiary structure similarity between the proteins from Plasmodium falciparum and human. Of 206 P. falciparum proteins that have previously been proposed as mediators of Plasmodium -human interactions, we propose that seven evolved to molecularly mimic a human protein. By expanding the approach to all P. falciparum proteins, we identified a further 386 potential mimics, with 51 proteins corroborated by additional biological data. These findings demonstrate a valuable application of AlphaFold-derived tertiary structural models, and we discuss key considerations for its effective use in other host-parasite systems.
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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) | 0.001 | 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 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".