Function of the Conserved S1 and KH Domains in Polynucleotide Phosphorylase
Bibliographic record
Abstract
We have examined the roles of the conserved S1 and KH RNA binding motifs in the widely dispersed prokaryotic exoribonuclease polynucleotide phosphorylase (PNPase). These domains can be released from the enzyme by mild proteolysis or by truncation of the gene. Using purified recombinant enzymes, we have assessed the effects of specific deletions on RNA binding, on activity against a synthetic substrate under multiple-turnover conditions, and on the ability of truncated forms of PNPase to form a minimal RNA degradosome with RNase E and RhlB. Deletion of the S1 domain reduces the apparent activity of the enzyme by almost 70-fold under low-ionic-strength conditions and limits the enzyme to digest a single substrate molecule. Activity and product release are substantially regained at higher ionic strengths. This deletion also reduces the affinity of the enzyme for RNA, without affecting the enzyme's ability to bind to RNase E. Deletion of the KH domain produces similar, but less severe, effects, while deletion of both the S1 and KH domains accentuates the loss of activity, product release, and RNA binding but has no effect on binding to RNase E. We propose that the S1 domain, possibly arrayed with the KH domain, forms an RNA binding surface that facilitates substrate recognition and thus indirectly potentiates product release. The present data as well as prior observations can be rationalized by a two-step model for substrate binding.
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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".