Fractionation factors reveal hidden frustration in an ancient allosteric module
Bibliographic record
Abstract
Protein kinase G (PKG) is an essential regulator of eukaryotic cyclic guanosine monophosphate (cGMP)-dependent intracellular signaling, controlling pathways that are often distinct from those regulated by cyclic adenosine monophosphate (cAMP). Specifically, the C-terminal cyclic-nucleotide-binding domain (CNB-B) of PKG has emerged as a critical module to control allostery and cGMP-selectivity in PKG. While key contributions to the cGMP-versus-cAMP selectivity of CNB-B were previously assessed, only limited knowledge is currently available on how cyclic nucleotide binding rewires the network of hydrogen bonds in CNB-B, and how such rewiring contributes to allostery and cGMP selectivity. To address this gap, we extend the comparative analysis of apo, cAMP- and cGMP-bound CNB-B to H/D fractionation factors (FFs), which are well-suited for assessing backbone hydrogen-bond strengths within proteins. Apo-vs-bound comparisons inform of perturbations arising from both binding and allostery, while cGMP-bound vs cAMP-bound comparisons inform of perturbations that are purely allosteric. The comparative FF analyses of the bound states revealed mixed patterns of hydrogen-bond strengthening and weakening, pointing to inherent frustration, whereby not all hydrogen bonds can be simultaneously stabilized. Interestingly, contrary to expectations, these patterns include a weakening of hydrogen bonds not only within critical recognition and allosteric elements of CNB-B, but also within elements known to undergo rigid-body movement upon cyclic nucleotide binding. These results suggest that frustration may contribute to the reversibility of allosteric conformational shifts by avoiding over-rigidification that may otherwise trap CNB-B in its active state. Considering that PKG CNB-B serves as a prototype for allosteric conformational switches, similar concepts may be applicable to allosteric domains in general.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".