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Record W2163161088 · doi:10.1073/pnas.0607748104

Folding and unfolding of a photoswitchable peptide from picoseconds to microseconds

2007· article· en· W2163161088 on OpenAlexaff
Janne A. Ihalainen, Jens Bredenbeck, Rolf Pfister, Jan Helbing, Lei Chi, Ivo H. M. van Stokkum, G. Andrew Woolley, Peter Hamm

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2007
Typearticle
Languageen
FieldMaterials Science
TopicPhotochromic and Fluorescence Chemistry
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPicosecondKineticsTemperature jumpFolding (DSP implementation)Downhill foldingProtein foldingChemistryMicrosecondCrystallographyChemical physicsPhi value analysisPeptideBiophysicsPhysicsPhysical chemistryLaser

Abstract

fetched live from OpenAlex

Using time-resolved IR spectroscopy, we monitored the kinetics of folding and unfolding processes of a photoswitchable 16-residue alanine-based alpha-helical peptide on a timescale from few picoseconds to almost 40 micros and over a large temperature range (279-318 K). The folding and unfolding processes were triggered by an ultrafast laser pulse that isomerized the cross linker within a few picoseconds. The main folding and unfolding times (700 ns and 150 ns, respectively, at room temperature) are in line with previous T-jump experiments obtained from similar peptides. However, both processes show complex, strongly temperature-dependent spectral kinetics that deviate clearly from a single-exponential behavior. Whereas in the unfolding experiment the ensemble starts from a well defined folded state, the starting ensemble in the folding experiment is more heterogeneous, which leads to distinctly different kinetics of the experiments, because they are sensitive to different regions of the energy surface. A qualitative agreement with the experimental data-set can be obtained by a model where the unfolded states act as a hub connected to several separated "misfolded" states with a distribution of rates. We conclude that a rather large spread of rates (k(1) : k(n) approximately 9) is needed to explain the experimentally observed stretched exponential response with stretching factor beta = 0.8 at 279 K.

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)0.002
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 score0.022
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.288
Teacher spread0.262 · 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

Citations96
Published2007
Admission routes1
Has abstractyes

Explore more

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