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Updated: Apr 28, 2026

Personalized Peptide Arrays for Detection of HLA Alloantibodies in Organ Transplantation
Published on: September 6, 2017
Mapping the peptide interaction fingerprint of the Behçet's disease-associated HLA-B∗51
Sema Zeynep Yilmaz1, Derman Basturk2, Ahmet Gul3
1Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Abstract:
The strongest genetic risk factor for Behçet's disease, a relapsing inflammatory disorder marked by recurrent mucocutaneous ulcers and uveitis, is HLA-B∗51:01, a class I major histocompatibility complex (MHC class I) allele that presents intracellular peptides to CD8+ T cells. The molecular mechanisms linking the peptide preferences of this allele to dysregulated immunity remain unclear, limiting efforts to design peptide-based modulators of antigen presentation. Here, we define HLA-B∗51:01's peptide selection rules by mapping the "interaction fingerprint" of 36 self-peptides using an extensive set of all-atom molecular dynamics simulations. These uncovered a conserved hydrophobic-polar blueprint tuned by peptide length. In silico pulling experiments performed at high-speed atomic force microscopy-like loading rates suggest a three-tier hierarchy of mechanical resilience: 9-mers resist the highest forces, 8-mers exhibit intermediate resistance, and 10-/11-mers rupture most easily. Our comprehensive analysis provides an atomistic framework for understanding the molecular mechanisms underlying the HLA-B∗51:01 pathobiology and offers quantitative parameters to guide the design of therapeutic peptides or small molecules to modulate antigen presentation in Behçet's disease.
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