Revving up COVID mRNA vaccines: Algorithm generates 128-fold increase in antibodies mRNA vaccines geneexpression predictivealgorithm biomedicalresearch geneprediction scientificinnovation COVID Nature
By Neha MathurMay 3 2023 In a recent article published in the journal Nature, researchers used a classical concept in computational linguistics to design a new algorithm, LinearDesign, which optimized the structural stability and codon usage of messenger ribonucleic acid sequences. For instance, using this algorithm, researchers could optimize mRNA sequences encoding the severe acute respiratory syndrome coronavirus 2 spike protein and use it in mRNA-based coronavirus disease 2019 vaccines.
Therefore, there is an urgent need for a principled mRNA design algorithm that simultaneously optimizes stability and codon usage of encoding mRNA sequences to improve protein expression. However, it is a tedious task considering the prohibitively large search space; there are ~10632 mRNA sequences to encode 1,273 amino acids of SARS-CoV-2 S glycoprotein due to inherent redundancies in the genetic code.
Specifically for the SARS-CoV-2 S protein, the team employed eight mRNA sequences and used the LinearDesign algorithm for seven sequences, i.e., A-G. They distributed these in the low-MFE design space and excluded the first five amino acids when running the algorithm. Though LinearDesign did not address untranslated region optimization per se, the mRNA molecules it designed did not interfere much with the structures of widely used UTRs.
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