Dynamics of Scabin toxin. A proposal for the binding mode of the DNA substrate
Bibliographic record
Abstract
Scabin is a mono-ADP-ribosyltransferase enzyme and is a putative virulence factor produced by the plant pathogen, Streptomyces scabies. Previously, crystal structures of Scabin were solved in the presence and absence of substrate analogues and inhibitors. Herein, experimental (hydrogen-deuterium exchange), simulated (molecular dynamics), and theoretical (Gaussian Network Modeling) approaches were systematically applied to study the dynamics of apo-Scabin in the context of a Scabin·NAD+·DNA model. MD simulations revealed that the apo-Scabin solution conformation correlates well with the X-ray crystal structure, beyond the conformation of the exposed, mobile regions. In turn, the MD fluctuations correspond with the crystallographic B-factors, with the fluctuations derived from a Gaussian network model, and with the experimental H/D exchange rates. An Essential Dynamics Analysis identified the dynamic aspects of the toxin as a crab-claw-like mechanism of two topological domains, along with coupled deformations of exposed motifs. The "crab-claw" movement resembles the motion of C3-like toxins and emerges as a property of the central β scaffold of catalytic single domain toxins. The exposure and high mobility of the cis side motifs in the Scabin β-core suggest involvement in DNA substrate binding. A ternary Scabin·NAD+·DNA model was produced via an independent docking methodology, where the intermolecular interactions correspond to the region of high mobility identified by dynamics analyses and agree with binding and kinetic data reported for wild-type and Scabin variants. Based on data for the Pierisin-like toxin group, the sequence motif Rβ1-RLa-NLc-STTβ2-WPN-WARTT-(QxE)ARTT emerges as a catalytic signature involved in the enzymatic activity of these DNA-acting toxins. However, these results also show that Scabin possesses a unique DNA-binding motif within the Pierisin-like toxin group.
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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 | 0.001 |
| Open science | 0.001 | 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".