Characterization of PGua<sub>4</sub>, a Guanidinium-Rich Peptoid that Delivers IgGs to the Cytosol via Macropinocytosis
Bibliographic record
Abstract
To investigate the structure-cellular penetration relationship of guanidinium-rich transporters (GRTs), we previously designed PGua 4, a five-amino acid peptoid containing a conformationally restricted pattern of eight guanidines, which showed high cell-penetrating abilities and low cell toxicity. Herein, we characterized the cellular uptake selectivity, internalization pathway, and intracellular distribution of PGua 4, as well as its capacity to deliver cargo. PGua 4 exhibits higher penetration efficiency in HeLa cells than in six other cell lines (A549, Caco-2, fibroblast, HEK293, Mia-PaCa2, and MCF7) and is mainly internalized by clathrin-mediated endocytosis and macropinocytosis. Confocal microscopy showed that it remained trapped in endosomes at low concentrations but induced pH-dependent endosomal membrane destabilization at concentrations ≥10 μM, allowing its diffusion into the cytoplasm. Importantly, PGua 4 significantly enhanced macropinocytosis and the cellular uptake and cytosolic delivery of large IgGs following noncovalent complexation. Therefore, in addition to its peptoid nature conferring high resistance to proteolysis, PGua 4 presents characteristics of a promising tool for IgG delivery and therapeutic applications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".