mRNA optimiser
mRNA optimiser optimizes mRNA secondary structure by adjusting minimum free energy (MFE) to improve protein synthesis while preserving the encoded polypeptide sequence.
Key Features:
- MFE modulation: Adjusts minimum free energy (MFE) upward or downward to strengthen or weaken mRNA secondary structure.
- Hairpin approximation: Uses an approach that approximates hairpin formation to achieve significant changes in structural strength, including reported increases in MFE up to 40%.
- Synonymous sequence preservation: Alters nucleotide sequence without changing the encoded amino acid sequence to maintain protein identity.
- Time-efficient processing: Implements a time-efficient computational process for structure optimization.
- Algorithmic independence: Operates without relying on existing algorithms that predict RNA secondary structures or generate sequences for predefined structures.
- Multi-objective optimization: Supports joint optimization of MFE with other gene expression metrics such as codon adaptation index (CAI).
- Genome-scale optimization: Enables optimization of secondary structures at a genomic level to enhance gene expression efficiency.
- Translation-focused rationale: Targets secondary-structure features that can impede ribosome initiation and progression to improve protein yield.
Scientific Applications:
- Gene expression enhancement: Improves protein synthesis by optimizing mRNA secondary structure to reduce structural impediments to translation.
- Multi-objective gene design: Enables combined optimization of MFE and codon adaptation index (CAI) for engineered genes.
- Genome-wide structural optimization: Applies secondary-structure optimization across genomes to increase expression efficiency in diverse biological systems.
Methodology:
Approximates hairpin formation and modifies nucleotide sequence via synonymous changes to alter MFE while preserving the amino acid sequence; implements a time-efficient computational process and explicitly does not use existing RNA secondary-structure prediction or sequence-generation algorithms.
Topics
Details
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Java
- Added:
- 8/3/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Gaspar P, Moura G, Santos MAS, Oliveira JL. mRNA secondary structure optimization using a correlated stem–loop prediction. Nucleic Acids Research. 2013;41(6):e73-e73. doi:10.1093/nar/gks1473. PMID:23325845. PMCID:PMC3616703.