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VaxPress: Codon Optimization for mRNA Vaccine Stability and Protein Expression
VaxPress is a codon optimizer platform for mRNA vaccine development that refines coding sequences to improve storage stability and in vivo protein expression. It starts from either a protein sequence or an RNA coding sequence and iteratively mutates it, scoring each candidate with a configurable fitness function. The documentation lists copyright by Seoul National University (2023) and the source is hosted at github.com/ChangLabSNU/VaxPress. VaxPress is released under the MIT License, while the optional LinearFold and LinearDesign components are licensed for non-commercial use only.
mRNA vaccines depend on the coding sequence: many different codon choices encode the same protein, but they differ in how the RNA folds, how stable it is in storage, and how well it is translated in cells. Searching this space by hand is impractical, and a single objective rarely captures everything that matters.
VaxPress treats these as a combined optimization problem and offers a pluggable interface, so additional properties can be added to the objective with a few lines of code.
Property | Detail |
|---|---|
Goal | Better storage stability and in vivo protein expression |
Input | FASTA coding sequence (or protein sequence with the protein flag) |
Default iterations | 10 (at least 500 recommended for thorough optimization) |
Folding engines | LinearDesign and LinearFold integration |
Optional score | iCodon predicted-stability weight |
License | MIT (LinearFold and LinearDesign non-commercial) |
How VaxPress Optimizes mRNA Coding Sequences
The documentation describes an optimization process driven by an objective function, with the mutation rate decreasing adaptively as the run proceeds.
Scoring functions: RNA folding, codon usage and other activity and production factors contribute to the fitness score, and the scheme is adjustable.
Custom scoring: user-defined scoring functions can be added.
LinearDesign initialization: optionally, optimization can start from a LinearDesign-based sequence.
Presets: parameters from a run are saved and can be reused with a preset option.
Multi-core and early stopping: runs can use several processes and stop early if no progress is seen over several consecutive cycles.
VaxPress Inputs and Outputs
Input and output are mandatory. A typical command optimizes a FASTA file for 1000 iterations on 32 processes. Setting iterations to 0 produces only an evaluation report of the given sequence.
Output file | Contents |
|---|---|
report.html | Summary of results and the optimization process |
best-sequence.fasta | The refined coding sequence |
checkpoints.tsv | Best sequences and evaluation results per iteration |
log.txt | Console logs |
parameters.json | Parameters used, reusable as a preset |
What is Tamarind Bio?
Tamarind Bio is a no-code bioinformatics platform built to give life scientists and researchers access to powerful computational tools. Many cutting-edge machine learning models are hard to deploy and use. Tamarind provides an intuitive, web-based environment that removes the complexity of high-performance computing, software dependencies and command-line interfaces.
The platform is designed for biologists, chemists and other researchers who may not have a background in programming or cloud infrastructure but want to run models on their own data. Key features include:
A user-friendly graphical interface for setting up and launching experiments
A robust API for integration into existing research pipelines
An automated system for managing and scaling computational resources
Tamarind treats information and data security as a top priority, as detailed in its Trust Center and Terms of Service.
Accelerating Discovery with VaxPress on Tamarind Bio
mRNA vaccine design: refine a coding sequence, starting from a protein or RNA sequence, for stability and expression.
Sequence evaluation: score an existing sequence without optimizing it by running zero iterations.
Custom objectives: weigh folding, codon usage and optional stability predictions against each other.
Reproducible runs: reuse saved parameters as presets across candidate antigens.
How to Use VaxPress on Tamarind Bio
Open the tool: log in to tamarind.bio and open VaxPress.
Provide the sequence: supply a coding sequence in FASTA format, or a protein sequence if exposed.
Set iterations: the default is 10, and at least 500 is recommended for thorough optimization.
Choose scoring options: if exposed, adjust fitness weights, folding engine, LinearDesign initialization, or the iCodon weight.
Run: submit the job.
Download results: retrieve the best sequence, the HTML report, checkpoints and parameters file.
Interpret: review the report and the per-iteration checkpoints to see how the score improved.
Use downstream: take the optimized sequence into construct design and experimental testing.
Things to Keep in Mind
LinearFold and LinearDesign are licensed for non-commercial use only, so use caution with those options in commercial work.
The iCodon option requires a working R, rpy2 and iCodon installation.
Short runs at the default 10 iterations are not thorough.
Optimized sequences are computational predictions and still need experimental validation.
Source: VaxPress documentation (version 0.4), Seoul National University, https://vaxpress.readthedocs.io/en/latest/. Code: https://github.com/ChangLabSNU/VaxPress. The repository cites Ju, Ku and Chang (2023, in preparation).