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Leaky Scanning

Leaky Scanning

During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA. Marilyn Kozak discovered that the sequence RCCAUGG (where R...

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Related Experiment Video

Updated: Jul 28, 2025

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

A Lean Reverse Vaccinology Pipeline with Publicly Available Bioinformatic Tools.

Bart Cuypers^1,2, Rino Rappuoli³, Alessandro Brozzi⁴

¹Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium.

Methods in Molecular Biology (Clifton, N.J.)

|May 31, 2023

Summary

Reverse vaccinology (RV) streamlines vaccine development by using bioinformatics to identify protein features for potential vaccine candidates. This study presents a simplified RV pipeline using accessible bioinformatics tools for broader application.

Keywords:

Antigen abundance B cell epitopes Bacteria Core proteome Reverse vaccinology Subcellular location T cell epitopes

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Last Updated: Jul 28, 2025

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Reverse Genetics to Engineer Positive-Sense RNA Virus Variants

Reverse Genetics to Engineer Positive-Sense RNA Virus Variants

Published on: June 9, 2022

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Published on: March 22, 2016

Area of Science:

Bioinformatics
Vaccinology
Computational Biology

Background:

Reverse vaccinology (RV) revolutionized vaccine development by integrating bioinformatics for antigen discovery.
Initially applied to *Neisseria meningitidis* serogroup B, RV has since been adapted for various bacterial vaccine targets.
Bioinformatics tools and methodologies in RV have evolved significantly over time.

Purpose of the Study:

To consolidate a streamlined pipeline for reverse vaccinology using publicly available bioinformatics tools.
To describe the practical application of these tools for extracting critical protein features for vaccine candidate selection.
To provide a foundation for utilizing extracted protein features in machine learning-based vaccine design approaches.

Main Methods:

Literature review and expert experience in reverse vaccinology.
Selection and integration of publicly available bioinformatics tools.
Description of methods for extracting protein features from sequence data.

Main Results:

A lean, reproducible reverse vaccinology pipeline has been established.
The pipeline facilitates the extraction of relevant protein features for vaccine candidate identification.
Extracted features are formatted for potential input into machine learning models.

Conclusions:

The presented RV pipeline offers a practical and accessible approach to vaccine candidate discovery.
This methodology enhances the efficiency of identifying potential targets for new vaccines.
The framework supports the integration of bioinformatics and machine learning in modern vaccinology.