When one peptide can speak to many immune systems.
A new computational approach developed by Prof.
@TomerHertz of
@bengurionu may help address one of the major challenges in T-cell-based vaccine design: creating immune responses that work across genetically diverse populations.
T cells do not recognize infected or cancerous cells directly. They recognize peptides presented on the cell surface by HLA molecules, one of the most diverse regions of the human genome, with more than 22,000 known genetic variants. As a result, a peptide that triggers a strong immune response in one person may be invisible to another.
Prof. Hertz, together with students Elinor Paar and Liel Cohen-Lavi, and additional researchers from
@ljiresearch, developed a computational method known as “Super HLA” to identify 9-amino-acid peptides capable of binding across multiple HLA supertypes.
The team began with more than 190,000 candidate peptides, selected 100 for synthesis and laboratory testing in the lab of
@SetteLab, and experimentally validated 24 as true “super-binders.” Of these, 21 bound to four or more HLA supertypes, and one bound to 9 out of 12.
Published in
@PNASNews, the findings open a path toward designing peptides with broad immunological coverage across genetically diverse populations, with potential relevance for cancer vaccines, vaccines against global infectious diseases, and populations that are underrepresented in existing reference datasets.
The roots of the idea go back nearly 15 years, to a conversation between Prof. Hertz and Dr.
@ChenYanover, then both postdoctoral fellows at
@fredhutch in Seattle. As Prof. Hertz notes, good ideas are worth continuing to dig into, even long after the first sketch was written on a whiteboard.
This is another example of how computational biology and immunology research at Ben-Gurion University of the Negev can open new directions for real-world biomedical innovation.
Additional Biotechnology & Bio-Convergence technologies from Ben-Gurion University of the Negev in the comments.
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