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Record W2769305135 · doi:10.1038/s41467-017-01996-1

Partially native intermediates mediate misfolding of SOD1 in single-molecule folding trajectories

2017· article· en· W2769305135 on OpenAlexafffund
Supratik Sen Mojumdar, Zackary N. Scholl, Derek R. Dee, Logan Rouleau, Uttam Anand, Craig R. Garen, Michael T. Woodside

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersAlberta Prion Research InstituteAlberta Innovates
KeywordsFolding (DSP implementation)Protein foldingSOD1ChemistryBiophysicsBiochemistryBiologySuperoxide dismutaseEnzyme

Abstract

fetched live from OpenAlex

Prion-like misfolding of superoxide dismutase 1 (SOD1) is associated with the disease ALS, but the mechanism of misfolding remains unclear, partly because misfolding is difficult to observe directly. Here we study the most misfolding-prone form of SOD1, reduced un-metallated monomers, using optical tweezers to measure unfolding and refolding of single molecules. We find that the folding is more complex than suspected, resolving numerous previously undetected intermediate states consistent with the formation of individual β-strands in the native structure. We identify a stable core of the protein that unfolds last and refolds first, and directly observe several distinct misfolded states that branch off from the native folding pathways at specific points after the formation of the stable core. Partially folded intermediates thus play a crucial role mediating between native and non-native folding. These results suggest an explanation for SOD1's propensity for prion-like misfolding and point to possible targets for therapeutic intervention.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.067
GPT teacher head0.383
Teacher spread0.316 · 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 source (direct Gemma or distilled Codex), 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

Citations79
Published2017
Admission routes2
Has abstractyes

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