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Macrocyclic Cell Penetrating Peptides: A Study of Structure-Penetration Properties

2015· article· en· W2048283075 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBioconjugate Chemistry · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryPenetration (warfare)BiophysicsStereochemistry

Abstract

fetched live from OpenAlex

Arginine-rich cell penetrating peptides are short cationic peptides able to cross biological membranes despite their peptidic character. In order to optimize their penetration properties and further elucidate their mechanisms of cellular entry, these peptides have been intensively studied for the last two decades. Although several parameters are simultaneously involved in the internalization mechanism, recent studies suggest that structural modifications influence cellular internalization. Particularly, backbone rigidification, including macrocyclization, was found to enhance proteolytic stability and cellular uptake. In the present work, we describe the synthesis of macrocyclic arginine-rich cell penetrating peptides and study their cellular uptake properties using a combination of flow cytometry and confocal microscopy. By varying ring size, site of cyclization, and stereochemistry of the arginine residues, we studied their structure-uptake relationship and showed that the mode and site of cyclization as well as the stereochemistry influence cellular uptake. This study led to the identification of a hepta-arginine macrocycle as efficient as its linear nona-arginine congener to enter cells.

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.

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 score0.004
Threshold uncertainty score0.736

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 head0.030
GPT teacher head0.244
Teacher spread0.214 · 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