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Record W4403716511 · doi:10.1021/jacs.4c09805

Structural Plasticity as a Driver of the Maturation of Pro-Interleukin-18

2024· article· en· W4403716511 on OpenAlexafffund
Jeffrey P. Bonin, James M. Aramini, Lewis E. Kay

Bibliographic record

VenueJournal of the American Chemical Society · 2024
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsChemistryPlasticityInterleukin 1βInterleukinCytokineInternal medicineComposite material

Abstract

fetched live from OpenAlex

Dynamics are often critical for biomolecular function. Herein we explore the role of motion in driving the maturation process of pro-IL-18, a potent pro-inflammatory cytokine that is cleaved by caspases-1 and -4 to generate the mature form of the protein. An NMR dynamics study of pro-IL-18, probing time scales over 12 orders of magnitude and focusing on 1 H, 13 C, and 15 N spin probes along the protein backbone and amino-acid side chains, reveals a plastic structure, with millisecond time scale dynamics occurring in a pair of β-strands, β1 and β*, that show large structural variations in a comparison of caspase-free and bound pro-IL-18 states. Fits of the relaxation data to a three-site model of exchange showed that the ground state secondary structure is maintained in the excited conformers, with the side chain of I48 that undergoes a buried-to-exposed conformational change in the caspase-free to -bound transition of pro-IL-18, sampling a more extensive range of torsion angles in one of the excited states characterized, suggesting partial unpacking in this region. Hydrogen exchange measurements establish the occurrence of an additional process, whereby strands β1 and β* locally unfold. Our data are consistent with a hierarchy of dynamic events that likely prime pro-IL-18 for facile caspase binding.

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 score0.051
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.015
GPT teacher head0.282
Teacher spread0.267 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Chemical SocietySame topicErythrocyte Function and PathophysiologyFrench-language works237,207