ReviewTrends in molecular medicine2014
A critical analysis of codon optimization in human therapeutics.
Review in Trends in molecular medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 187 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
187 citing papers in PubMed.
- Trial
- Codon Optimality Modulates Cellular Stress and Innate Immune Responses Triggered by Exogenous RNAs.Journal of molecular biology · 2026Article
- RNA therapeutics: current status and future directions.Signal transduction and targeted therapy · 2026Review
- Auto-SMART: a web-based platform for repair-template design for CRISPR/Cas9 homology-directed editing.bioRxiv : the preprint server for biology · 2026Article
- Synonymous Gene Recoding Affects the Accuracy of Protein Quantification Measurements.The AAPS journal · 2026Article
- Double-stranded DNA donors and CRISPR-Cas9 for universal correction of mutations causing cystic fibrosis in human airway cells.Molecular therapy. Nucleic acids · 2026Article
- Enhancing protein expression in humans through codon optimization with transformer and contrastive learning.Molecular therapy. Nucleic acids · 2026Article
- seq2ribo: structure-aware integration of machine learning and simulation to predict ribosome location profiles from RNA sequences.Bioinformatics (Oxford, England) · 2026Article
- Deep learning based attention enhanced phylogenetic radial basis function networks (AE-PRBFN) for genomic codon usage classification across species.Scientific reports · 2026Article
- Multilayered nucleotide organization reveals purifying selection and host-driven adaptation in CPV and FPV.BMC veterinary research · 2026Article
- In silico design and immunogenicity evaluation of a multi-epitope vaccine against EV-A71.Journal of computer-aided molecular design · 2026Article
- seq2ribo: Structure-aware integration of machine learning and simulation to predict ribosome location profiles from RNA sequences.bioRxiv : the preprint server for biology · 2026Article
- VaxLab: integrated platform for rapid multistrategy mRNA vaccine design.Experimental & molecular medicine · 2026Article
- Purifying recombinant proteins from Nicotiana benthamiana for structural studies.Nature protocols · 2026Review
- mRNA-engineered CRISPR-Cas epigenetic editors enable durable and efficient gene silencingInnovation (Cambridge (Mass.)) · 2026Article
- Pichia-CLM: A language model-based codon optimization pipeline forProceedings of the National Academy of Sciences of the United States of America · 2026Article
- Advancing codon language modeling with synonymous codon constrained masking.Nucleic acids research · 2026Article
- mRNA vaccines in cancer immunotherapy: current progress and perspectives in solid tumors and hematologic malignancies.MedScience · 2026Review
- ColiFormer: A Transformer-Based Codon Optimization Model Balancing Multiple Objectives for EnhancedBioengineering (Basel, Switzerland) · 2026Article
- Systematic Evaluation of Vector Sequence Elements in Isogenic CHO Cells for Improved Antibody Production.ACS synthetic biology · 2026Article
127 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Codon optimization describes gene engineering approaches that use synonymous codon changes to increase protein production. Applications for codon optimization include recombinant protein drugs and nucleic acid therapies, including gene therapy, mRNA therapy, and DNA/RNA vaccines. However, recent reports indicate that codon optimization can affect protein conformation and function, increase immunogenicity, and reduce efficacy. We critically review this subject, identifying additional potential hazards including some unique to nucleic acid therapies. This analysis highlights the evolved complexity of codon usage and challenges the scientific bases for codon optimization. Consequently, codon optimization may not provide the optimal strategy for increasing protein production and may decrease the safety and efficacy of biotech therapeutics. We suggest that the use of this approach is reconsidered, particularly for in vivo applications.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.