Abstract

Small interfering ribonucleic acid (siRNA)‐based gene knockdown is an effective tool for gene screening and therapeutics. However, the use of nonviral methods has remained an enormous challenge in neural cells. A strategy is reported to design artificial noncationic modular peptides with amplified affinity for siRNA via supramolecular assembly that shows efficient protein knockdown in neural cells. By solid phase synthesis, a sequence that binds specifically double‐stranded ribonucleic acid (dsRNA) with a self‐assembling peptide for particle formation is integrated. These supramolecular particles can be further functionalized with bioactive sequences without affecting their biophysical properties. The peptide carrier is found to silence efficiently up to 83% of protein expression in primary astroglial and neuronal cell cultures without cytotoxicity. In the case of neurons, a reduction in electrical activity is observed once the presynaptic protein synaptophysin is downregulated by the siRNA–peptide particles. The results demonstrate that the supramolecular particles offer an siRNA delivery platform for efficient nonviral gene screening and discovery of novel therapies for neural cells.

Highlights

  • Small interfering ribonucleic acid-based gene knockdown is an effective tool for gene screening and therapeutics

  • We report on a supramolecular particle that effectively transfects neural cells with very high efficiency and with minimal toxicity

  • These findings suggest that fusion of the peptide P2 to P3 helped to encapsulate Small interfering ribonucleic acid (siRNA), generating an effective binding capacity comparable to the much larger peptide doublestranded RNA-binding domain (dsRBD)

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Summary

Introduction

Small interfering ribonucleic acid (siRNA)-based gene knockdown is an effective tool for gene screening and therapeutics. Our strategy was to transfect neural cells with P4 particles carrying the positive siRNA for GFAP or synaptophysin for astroglial or neuronal cell cultures, respectively.

Results
Conclusion
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