2025/01/24 by Sizhen Li, Shahriar Noroozizadeh, Saeed Moayedpour +7 · 1 voice · 1 citation
Biochemistry, Genetics and Molecular Biology · Immunology and Microbiology · Medicine · #RNA and protein synthesis mechanisms #Antimicrobial Peptides and Activities #Viral gastroenteritis research and epidemiology
paper · doi:10.1093/nar/gkaf044
openalex publication_date 2025/01/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
The success of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) messenger RNA (mRNA) vaccine has led to increased interest in the design and use of mRNA for vaccines and therapeutics. Still, selecting the most appropriate mRNA sequence for a protein remains a challenge. Several recent studies have shown that the specific mRNA sequence can have a significant impact on the translation efficiency, half-life, degradation rates, and other issues that play a major role in determining vaccine efficiency. To enable the selection of the most appropriate sequence, we developed mRNA-LM, an integrated small language model for modeling the entire mRNA sequence. mRNA-LM uses the contrastive language-image pretraining integration technology to combine three separate language models for the different mRNA segments. We trained mRNA-LM on millions of diverse mRNA sequences from several different species. The unsupervised model was able to learn meaningful biology related to evolution and host-pathogen interactions. Fine-tuning of mRNA-LM allowed us to use it in several mRNA property prediction tasks. As we show, using the full-length integrated model led to accurate predictions, improving on prior methods proposed for this task.