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Combinatorial Discovery of RAFT Cationic Polymers for mRNA Delivery: Structure-Function Insights from High-Throughput
Wenting Yang1, Shangqian Li2, Siqi Yu3
1Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St Lucia, Queensland 4072, Australia.
Biomacromolecules
|October 7, 2025
Summary
New cationic polymers show superior mRNA delivery compared to lipid nanoparticles. Machine learning identified key polymer features for enhanced cellular uptake and transfection efficiency, guiding future therapeutic design.
Area of Science:
- Polymer Chemistry
- Biotechnology
- Nanomedicine
Background:
- Cationic polymers offer potential advantages over lipid nanoparticles for messenger RNA (mRNA) delivery.
- Developing effective and safe mRNA delivery systems is crucial for advancing nucleic acid-based therapeutics.
Purpose of the Study:
- To synthesize and evaluate a library of methacrylate-based cationic polymers for mRNA delivery.
- To identify lead polymers with superior mRNA delivery performance.
- To elucidate structure-function relationships governing polymer-mRNA complex interactions and biological outcomes.
Main Methods:
- Combinatorial RAFT polymerization to create diverse cationic polymers.
- Comprehensive characterization of polymer-mRNA complexation.
- Systematic evaluation of cellular uptake, cytotoxicity, and mRNA transfection efficiency using high-throughput screening.
- Machine learning analysis to predict biological responses based on polymer properties.
Main Results:
- Identified several lead cationic polymers demonstrating significantly enhanced mRNA delivery efficacy.
- These novel polymers outperformed benchmark materials like polyethylenimine (PEI) and Lipofectamine.
- Machine learning models revealed key polymer attributes predictive of cellular uptake, cytotoxicity, and transfection efficiency.
Conclusions:
- Tertiary amine-containing methacrylate-based cationic polymers are effective mRNA delivery vehicles.
- Structure-property relationships were uncovered, enabling rational design of next-generation mRNA delivery systems.
- This work provides a data-driven approach for developing superior cationic polymers for therapeutic mRNA delivery.
