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Record W2020091506 · doi:10.1021/bi026856t

Prevention of Peptide Fibril Formation in an Aqueous Environment by Mutation of a Single Residue to Aib

2003· article· en· W2020091506 on OpenAlexafffund
Janet R. Kumita, Chris J. Weston, Lin‐P'ing Choo‐Smith, G. Andrew Woolley, Oliver S. Smart

Bibliographic record

VenueBiochemistry · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsNational Research Council Institute for BiodiagnosticsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Birmingham
KeywordsFibrilChemistryPeptideCircular dichroismThioflavinRandom coilResidue (chemistry)Beta sheetAlanineStereochemistryCrystallographyPeptide sequencePeptide ConformationAlpha helixProtein structureHelix (gastropod)Amino acidBiochemistry

Abstract

fetched live from OpenAlex

The behavior of a number of 16 residue polypeptides with a sequence Acetyl-EACARXZAACEAAARQ-amide, where X = V or A and Z = A or Aib, is studied under aqueous conditions. It is shown that the substitution of a single alanine residue by alpha-aminoisobutyric acid (Aib) completely alters both the conformation and the aggregation properties of the peptides. The Ala-Ala (X,Z = A,A) peptide is shown by circular dichroism and FTIR methods to adopt a predominately beta-sheet conformation. Furthermore, the peptide has limited solubility and is shown to form fibrils by electron microscopy and thioflavin T binding assays. In contrast, a single substitution at the center of peptide of alanine to Aib (X,Z = A,Aib) completely abolishes fibril formation and alters the conformation to a mixture of random coil and alpha-helix. The results show that Aib is a strong beta-sheet disrupter that is also able to adopt a helical conformation. This is linked to its role in peptaibol antibiotics. Aib provides an attractive alternative to proline and other substitutions in producing peptide variants with a lower tendency to produce fibril aggregates.

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 score0.002
Threshold uncertainty score0.335

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 head0.224
Teacher spread0.217 · 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

Citations27
Published2003
Admission routes2
Has abstractyes

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