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Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

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Aminoacyl-tRNA synthetases are present in both eukaryotes and bacteria. Though eukaryotes have 20 different aminoacyl-tRNA synthetases to couple to 20 amino acids, many bacteria do not have genes for all of these aminoacyl-tRNA synthetases. Despite this, they still use all 20 amino acids to synthesize their proteins. For instance, some bacteria do not have the gene encoding the enzyme that couples glutamine with its partner tRNA. In these organisms, one enzyme adds glutamic acid to all of the...

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Related Experiment Video

Updated: Jul 23, 2025

Genome-wide Analysis of Aminoacylation Charging Levels of tRNA Using Microarrays

Genome-wide Analysis of Aminoacylation Charging Levels of tRNA Using Microarrays

Published on: June 18, 2010

gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm.

Ali Mostafa Anwar¹, Saif M Khodary², Eman Ali Ahmed^1,3

¹Proteomics and Metabolomics Research Program, Basic Research Department, Children's Cancer Hospital 57357 (CCHE-57357), Cairo, Egypt.

Frontiers in Molecular Biosciences

|July 20, 2023

Summary

The genetic tRNA adaptation index (gtAI) improves translation efficiency prediction by using a genetic algorithm for optimal weighting. This novel method enhances accuracy across diverse genomes compared to previous approaches.

Keywords:

codon usage codon usage analysis molecular evolution tRNA adaptation index translational selection

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Last Updated: Jul 23, 2025

Genome-wide Analysis of Aminoacylation Charging Levels of tRNA Using Microarrays

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Published on: June 18, 2010

Identifying Amino Acid Overproducers Using Rare-Codon-Rich Markers

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An In Vitro Assay to Detect tRNA-Isopentenyl Transferase Activity

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Published on: October 8, 2018

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

The tRNA adaptation index (tAI) measures translation efficiency using codon-tRNA wobble interactions.
Previous methods like species-specific tAI (stAI) had limitations in optimizing weighting values and accuracy across different species.

Purpose of the Study:

To develop a novel, accurate, and species-agnostic method for computing the tRNA adaptation index (tAI).
To improve the prediction of protein abundance and correlation with codon adaptation index (CAI).

Main Methods:

Developed genetic tAI (gtAI), a Python package utilizing a genetic algorithm to optimize S_ values for codon-tRNA wobble interactions.
Implemented a new codon usage-based workflow for calculating tAI across all three domains of life.

Main Results:

gtAI significantly improved the correlation with codon adaptation index (CAI).
gtAI demonstrated superior prediction of protein abundance compared to the stAI method.
The genetic algorithm successfully optimized S_ weights for better tAI computation.

Conclusions:

The gtAI method offers a more robust and accurate approach to calculating translation efficiency.
gtAI provides a valuable tool for genomic and proteomic research across diverse organisms.