Mechanism of allosteric inhibition in the Plasmodium falciparum cGMP-dependent protein kinase
Bibliographic record
Abstract
Most malaria deaths are caused by the protozoan parasite Plasmodium falciparum . Its life cycle is regulated by a cGMP-dependent protein kinase ( Pf PKG), whose inhibition is a promising antimalaria strategy. Allosteric kinase inhibitors, such as cGMP analogs, offer enhanced selectivity relative to competitive kinase inhibitors. However, the mechanisms underlying allosteric Pf PKG inhibition are incompletely understood. Here, we show that 8-NBD-cGMP is an effective Pf PKG antagonist. Using comparative NMR analyses of a key regulatory domain, Pf D, in its apo , cGMP-bound, and cGMP analog–bound states, we elucidated its inhibition mechanism of action. Using NMR chemical shift analyses, molecular dynamics simulations, and site-directed mutagenesis, we show that 8-NBD-cGMP inhibits Pf PKG not simply by reverting a two-state active versus inactive equilibrium, but by sampling also a distinct inactive "mixed" intermediate. Surface plasmon resonance indicates that the ability to stabilize a mixed intermediate provides a means to effectively inhibit Pf PKG, without losing affinity for the cGMP analog. Our proposed model may facilitate the rational design of Pf PKG-selective inhibitors for improved management of malaria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".