Design and characterization of a new peptide vector for short interfering RNA delivery
Bibliographic record
Abstract
RNA interference holds tremendous potential as one of the most powerful therapeutic strategies. However, the properties of short interfering RNA (siRNA), such as hydrophilicity, negative charge, and instability in serum have limited its applications; therefore, significant efforts have been undertaken to improve its cellular uptake. Cell penetrating peptides have been utilized to deliver various biologically active molecules, such as proteins, liposomes, nanoparticles, peptide nucleic acids, and recently small interfering RNAs. Here, we introduce a new cell penetrating peptide GL1(Ac-GLWRAWLWKAFLASNWRRLLRLLR-NH2) to improve the intracellular uptake of siRNA. This peptide consists of four tryptophan residues that facilitated its binding with the cell membrane, five arginine residues and one lysine residue which are positively charged at physiological pH, which induced the formation of peptide-siRNA complexes and enhanced the affinity of the peptide and cell membrane. Moreover, GL1 adopted helical secondary structure due to the altered distribution of polar and nonpolar residues in the sequence. In this study, we investigated the effect of peptide/siRNA molar ratio on the particle size, surface charge, secondary structure, and uptake efficiency. The results showed that GL1 formed stable complexes with siRNA mainly through electrostatic interaction and hydrophobic interaction, and the complexes displayed a spherical shape with the size of ~100 nm and positive surface charge. Utilizing the techniques of fluorescence microscopy and flow cytometry, the intracellular localization of Cy3-labeled GAPDH siRNA was visualized and the cellular uptake was quantified. It is worth noting that in the serum free environment, compared to Lipofectamine 2000, GL1 achieved higher cellular uptake of siRNA (~95%); in the presence of serum, GL1 retained the same level of siRNA cellular uptake (~84%) as Lipofectamine 2000. In addition, the viability of cells treated by GL1 in all studied molar ratios was >85%, which was significantly higher than that treated by Lipofectamine 2000 (~70%). Taken together, the peptide GL1 demonstrated promise as a siRNA delivery system.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".