Overlapping Epitopes to Develop Safe, Better-Suited Vaccines

Vaccine development aims at protecting as many people as possible from infections. Short protein fragments of pathogens, or epitopes, are seen as a promising new approach for vaccine development. In Cell Systems, bioinformaticians from Heinrich Heine University Düsseldorf (HHU) recently published a method for identifying those epitopes that promise safe immunization across the broadest possible population group. They have also computed vaccine candidates against SARS-CoV-2 using their HOGVAX tool.

Everyone has a unique immune system: Depending on their infection history, the immune system is trained to handle and react to different proteins. “This is a fundamental problem of vaccines based on epitopes,” explains Gunnar Klau, PhD, professor and chair of Algorithmic Bioinformatics at HHU. Together with his PhD student Sara Schulte and Alexander Dilthey, PhD, a professor from the Institute of Medical Microbiology and Hospital Hygiene, Klau considered a new approach to developing such vaccines.

The chef, the cookbook, and the vaccine

Professor Klau compares the problem with a chef who needs to create a new dish for a large event: “Some guests have allergies, while others do not like certain ingredients, so the chef needs to select ingredients that as many of the guests as possible can eat and will enjoy.”

Translated to vaccine development, this means that they are seeking epitopes that trigger a good immune response in as many people as possible. This is necessary because it is not possible to pack an unlimited number of protein fragments into a vaccine so that the various immune systems can seek out the sequences suitable for them—the carrier medium simply does not have sufficient capacity.

The HOGVAX tool

The team of three researchers took a special approach with their bioinformatic tool “HOGVAX.” Schulte said, “Instead of stringing the epitopes for the vaccine together end-to-end, we use identical sequences at the beginning and end of the epitopes so we can overlay them. The identical section, known as the ‘overlap’, is thus only represented once in the vaccine, which enables us to save a huge amount of space.” This in turn enables many more epitopes to be included in a vaccine.

In order to manage the epitopes and their longest overlaps efficiently, the researchers use a data structure known as a “hierarchical overlap graph” (HOG). Klau said, “To stay with the cooking analogy, HOG corresponds to a compressed or shrunk cookbook, from which the chef can now select the recipes that are suitable for all guests.”

“As a test, we applied HOGVAX to data for SARS-CoV-2 and were able to integrate significantly more epitopes than other tools. According to our calculations, we would be able to reach—and immunize—more than 98 percent of the world population,” Dilthey said.

Schulte comments on the further perspectives for their results: “In the future, we will work on adapting HOGVAX for use in cancer therapy. The aim here is to develop agents specifically designed for individual patients that attack tumor cells in a targeted manner.”

- This press release was originally published on the Heinrich-Heine-Universität Düsseldorf website