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Record W2014278139 · doi:10.1080/10611860600763079

Neuronal affinity of a C7C loop peptide identified through phage display

2006· article· en· W2014278139 on OpenAlexfundno aff
Thais Federici, James K. Liu, Qingshan Teng, Mary E. Garrity‐Moses, Jun Yang, Nicholas M. Boulis

Bibliographic record

VenueJournal of drug targeting · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsnot available
FundersUniversity of TorontoNational Science Council
KeywordsBiopanningPhage displayPeptidePeptide libraryMolecular biologyBiologyImmunofluorescenceChemistryCell biologyPeptide sequenceAntibodyBiochemistryGeneGenetics

Abstract

fetched live from OpenAlex

Phage display is a promising tool for the screening of peptides with high affinity for specific cells. Here we describe a novel peptide with neuronal affinity isolated from a C7C library. We designed a two-tiered biopanning strategy initially selecting for ganglioside binding and subsequently selecting for binding to PC12 cells. At the completion of biopanning, 54.8% of phage clones bore the identical peptide (Tet.C7C.1). Immunofluorescence confirmed selective binding of this clone to differentiated PC12 cells. Tet.C7C.1 was synthesized and fluorescein conjugated. The synthetic peptide binds neuronal cell lines (SH-SY5Y, NSC-34 and PC12 cells) and tissue (DRG and spinal cord). The C7C structure creates a loop that minimizes the impact of peptide insertion on the confirmation of the recipient protein. Small loop peptides have the ideal characteristics for modification of viral vector capsids without undermining genome packaging. The neuronal binding properties of this peptide may be applied in the development of neurotropic viral vectors.

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 score0.009
Threshold uncertainty score0.518

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 science0.0000.000
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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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

Citations4
Published2006
Admission routes1
Has abstractyes

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