Divergent allostery reveals critical differences between structurally homologous regulatory domains of Plasmodium falciparum and human protein kinase G
Bibliographic record
Abstract
Malaria is a life-threatening infectious disease primarily caused by the Plasmodium falciparum parasite. The increasing resistance to current antimalarial drugs and their side effects has led to an urgent need for novel malaria drug targets, such as the P. falciparum cGMP-dependent protein kinase (pfPKG). However, PKG plays an essential regulatory role also in the human host. Human cGMP-dependent protein kinase (hPKG) and pfPKG are controlled by structurally homologous cGMP-binding domains (CBDs). Here, we show that despite the structural similarities between the essential CBDs in pfPKG and hPKG, their respective allosteric networks differ significantly. Through comparative analyses of chemical shift covariance analyses, molecular dynamics simulations, and backbone internal dynamics measurements, we found that conserved allosteric elements within the essential CBDs are wired differently in pfPKG and hPKG to implement cGMP-dependent kinase activation. Such pfPKG versus hPKG rewiring of allosteric networks was unexpected because of the structural similarity between the two essential CBDs. Yet, such finding provides crucial information on which elements to target for selective inhibition of pfPKG versus hPKG, which may potentially reduce undesired side effects in malaria treatments.
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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".