VaxLab: integrated platform for rapid multistrategy mRNA vaccine design.

Area of Science:

• Biotechnology
• Bioinformatics
• Vaccine Development

Background:

• Messenger RNA (mRNA) vaccine efficacy is significantly influenced by sequence optimization.
• Designing optimal mRNA sequences is complex due to intricate cellular RNA regulatory mechanisms.

Purpose of the Study:

• To introduce VaxLab, an open-source web platform that streamlines the entire mRNA vaccine design-to-synthesis workflow.
• To provide a unified interface integrating multiple codon optimization algorithms and sequence design tools.

Main Methods:

• VaxLab incorporates four distinct codon optimization algorithms: codon usage matching, secondary structure design, and deep generative models.
• It offers generative models and a predefined library for designing 5' and 3' untranslated regions.
• The platform evaluates designed sequences using ten predictive metrics for RNA stability, protein expression, and manufacturing risks, with an integrated editor for adjustments.

Main Results:

• VaxLab completed the design workflow for influenza hemagglutinin variants in under 5 minutes per sequence.
• Optimized mRNA variants demonstrated up to 9.5-fold higher protein expression in HCT116 cells compared to wild-type sequences.
• Most optimized variants achieved at least a 2.9-fold increase in protein expression.

Conclusions:

• VaxLab offers an integrated optimization workbench that accelerates mRNA vaccine design.
• It enables principled selection among multiple optimization techniques informed by RNA regulation.
• The platform facilitates faster development of more effective mRNA vaccines.