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Solution structure of the catalytic domain of RICH protein from goldfish

2007· article· en· W1859819500 on OpenAlexaff
Guennadi Kozlov, A. Yu. Denisov, Ekaterina Pomerantseva, Michel Gravel, Peter E. Braun, Kalle Gehring

Bibliographic record

VenueFEBS Journal · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsMcGill UniversityWilliam Osler Health System
FundersUniversity of Michigan
KeywordsAntiparallel (mathematics)HydrolaseNucleotideBiologyPhosphodiesteraseResidual dipolar couplingProtein structureActive siteBiophysicsBiochemistryStereochemistryCell biologyChemistryEnzymeNuclear magnetic resonance spectroscopy

Abstract

fetched live from OpenAlex

Regeneration-induced CNPase homolog (RICH) is an axonal growth-associated protein, which is induced in teleost fish upon optical nerve injury. RICH consists of a highly acidic N-terminal domain, a catalytic domain with 2',3'-cyclic nucleotide 3'-phosphodiesterase (CNPase) activity and a C-terminal isoprenylation site. In vitro RICH and mammalian brain CNPase specifically catalyze the hydrolysis of 2',3'-cyclic nucleotides to produce 2'-nucleotides, but the physiologically relevant in vivo substrate remains unknown. Here, we report the NMR structure of the catalytic domain of goldfish RICH and describe its binding to CNPase inhibitors. The structure consists of a twisted nine-stranded antiparallel beta-sheet surrounded by alpha-helices on both sides. Despite significant local differences mostly arising from a seven-residue insert in the RICH sequence, the active site region is highly similar to that of human CNPase. Likewise, refinement of the catalytic domain of rat CNPase using residual dipolar couplings gave improved agreement with the published crystal structure. NMR titrations of RICH with inhibitors point to a similar catalytic mechanism for RICH and CNPase. The results suggest a functional importance for the evolutionarily conserved phosphodiesterase activity and hint of a link with pre-tRNA splicing.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.222

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 head0.007
GPT teacher head0.228
Teacher spread0.222 · 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

Citations15
Published2007
Admission routes1
Has abstractyes

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