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In silico study optimized mRNA sequences for vaccines and therapeutics, suggesting AI methods enhance design accuracy.
This in silico study explored the optimization of therapeutic RNA modeling using AI (AlphaFold3, Boltz-1, Chai-1). An assembly method combined high-confidence regions to model complex sequences. Quality was evaluated using five standardized metrics (secondary structure, stability, translation, immunogenicity, and production). Simulations and bioinformatics analyses were used to assess the stability and function of the optimized structures. The objective was to develop more accurate and comparable modeling methodologies for therapeutic RNA design, while recognizing the need for subsequent experimental validation.
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Souza et al. (2025) studied this question.
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