GASCO: genetic algorithm simulation for codon optimization.

In Silico Biol

GN Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology, Mall Road, Delhi, India.

Published: November 2008

Codon optimization is a generic technique to achieve optimum expression of a foreign gene in the host's cell system. Selection of optimum codons depends on codon usage of the host genome and the presence of several desirable and undesirable sequence motifs. Searching these motifs in all possible combinations of the codons increases the search space exponentially with respect to sequence length. GASCO is an algorithm developed for the optimum codon selection using genetic algorithms. The algorithm reduces the search space and provides an approximate solution to the problem. The algorithm has applications in DNA vaccine design for successfully eliciting potent immune responses and synthetic gene design for metabolic pathway engineering. The software for the proposed algorithm is available on http://miracle.igib.res.in/gasco/.

Download full-text PDF

Source

Publication Analysis

Top Keywords

codon optimization
8
search space
8
algorithm
5
gasco genetic
4
genetic algorithm
4
algorithm simulation
4
codon
4
simulation codon
4
optimization codon
4
optimization generic
4

Similar Publications

Background/objectives: Approved mRNA vaccines commonly use sequences modified with pseudouridine to enhance translation efficiency and mRNA stability. However, this modification can result in ribosomal frameshifts, reduced immunogenicity, and higher production costs. This study aimed to explore the potential of unmodified mRNA sequences for varicella-zoster virus (VZV) and evaluate whether codon optimization could overcome the limitations of pseudouridine modification.

View Article and Find Full Text PDF

Background: Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe respiratory illness in humans and currently lacks an approved vaccine. The Newcastle disease virus (NDV) vector is a well-established, safe, and effective platform for vaccine development. With recent advancements in stabilizing coronavirus spike proteins to enhance their antigenicity, this study aimed to determine whether modifications to the MERS-CoV spike protein could improve its presentation on NDV particles, allowing the resulting virus to be used as an inactivated vaccine.

View Article and Find Full Text PDF

Members of the families Thermosynechococcaceae and Thermostichaceae are well-known unicellular thermophilic cyanobacteria and a non-thermophilic genus was newly classified into the former. Analysis of the codon usage bias (CUB) of cyanobacterial species inhabiting different thermal and non-thermal niches will benefit the understanding of their genetic and evolutionary characteristics. Herein, the CUB and codon context patterns of protein-coding genes were systematically analyzed and compared between members of the two families.

View Article and Find Full Text PDF

Human rhinovirus C (HRV-C) is a significant contributor to respiratory tract infections in children and is implicated in asthma exacerbations across all age groups. Despite its impact, there is currently no licensed vaccine available for HRV-C. Here, we present a novel approach to address this gap by employing immunoinformatics techniques for the design of a multi-epitope-based vaccine against HRV-C.

View Article and Find Full Text PDF

Construction and iterative redesign of synXVI a 903 kb synthetic Saccharomyces cerevisiae chromosome.

Nat Commun

January 2025

School of Natural Sciences, and ARC Centre of Excellence in Synthetic Biology, Macquarie University, Sydney, Australia.

The Sc2.0 global consortium to design and construct a synthetic genome based on the Saccharomyces cerevisiae genome commenced in 2006, comprising 16 synthetic chromosomes and a new-to-nature tRNA neochromosome. In this paper we describe assembly and debugging of the 902,994-bp synthetic Saccharomyces cerevisiae chromosome synXVI of the Sc2.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!