A structural investigation of novel fungal polyglycine hydrolases
Bibliographic record
Abstract
Polyglycine hydrolases (PGH) are a family of fungal proteases that are known to cleave the polyglycine linker of Zea mays chitinase, ChitA, thwarting one mechanism of plant defense against fungal infection. Previously, little was known at the atomic level about the interaction between these proteases and their target. There has been limited biochemical characterization and no structural characterization of this family of proteases. In this work, we analyze the atomic structure of one of these polyglycine hydrolases, Fvan-cmp. The structure was solved by X-ray crystallography using a de novo RoseTTAFold model. We report models for the other identified polyglycine hydrolases utilizing the previously determined structure, as well as insights into features likely involved in the catalytic mechanism. The PGH structural characterization identified a two-domain structure, simply named N- and C- domain. The N-domain is a novel tertiary fold found throughout all kingdoms but functionally unidentified. The C-domain shares structural similarities with Class C β-lactamases including the conserved active site motifs and catalytic residues. Utilizing a combination of in vitro and in silico methods, we propose a PGH-ChitA complex model that is supported by previous understanding of PGHs and the structural data. Throughout this work, we discuss the merits and limitations of current in silico methods with a focus on de novo protein modelling and protein-protein docking methods.
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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".