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Record W7062079771

A structural investigation of novel fungal polyglycine hydrolases

2023· dissertation· en· W7062079771 on OpenAlexfundno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicGyrotron and Vacuum Electronics Research
Canadian institutionsnot available
FundersMitacs
KeywordsIn silicoProteasesDocking (animal)LinkerCharacterization (materials science)Homology modelingCleaveProtein structure
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.944

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.245
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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