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Record W2162164482 · doi:10.1021/jp0740301

Single-Walled Carbon Nanotube Binding Peptides:  Probing Tryptophan's Importance by Unnatural Amino Acid Substitution

2007· article· en· W2162164482 on OpenAlexaff
Zhengding Su, Kenneth Mui, Elisabeth Daub, Tong Leung, John F. Honek

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2007
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTryptophanCarbon nanotubePeptideHistidineAmino acidChemistryResidue (chemistry)AlanineLysineStereochemistryCombinatorial chemistryOrganic chemistryNanotechnologyBiochemistryMaterials science

Abstract

fetched live from OpenAlex

Peptides selected from phage-displayed libraries have been found to exhibit high-affinity binding to carbon nanotubes including single-walled carbon nanotubes (SWNTs), multi-walled carbon nanotubes, and single-walled carbon nanohorns. One unique feature of these peptides is that their amino acid sequences are rich in tryptophan and histidine residues. The aim of this study was to investigate the importance of the tryptophan residue in a newly identified SWNT-binding peptide, UW-1, which contains the motif, XTHXXPWTX, where X is any amino acid. Tryptophan was altered in the following ways: mutation to alanine or substitution with three unnatural tryptophan analogues, i.e., 5-fluorotryptophan, 5-hydroxytryptophan, and 7-azatryptophan. Analysis of experimental and computational data suggests that the highest occupied molecular orbital of the tryptophan residue in the peptide interacts with the lowest unoccupied molecular orbital from the SWNT. This information should be important in permitting modulation of peptide affinities to these nanomaterials.

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)0.001
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 score0.001
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.010
GPT teacher head0.240
Teacher spread0.230 · 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

Citations54
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry BSame topicCarbon Nanotubes in CompositesFrench-language works237,207