New computational method aims to lower risk factors in stem cell transplantation

August 20, 2012

Researchers from the University of Chicago/Argonne National Laboratory Computation Institute, University of Chicago’s Department of Pathology and Argonne’s Midwest Center for Structural Genomics have developed a new structure-based methodology to model peptide-human leukocyte antigen (HLA) binding interactions.

Prediction of peptide binding to human leukocyte antigen molecules is essential to a wide range of clinical entities from vaccine design to stem cell transplant compatibility.

The effect on binding activity across a large set of high-affinity peptides is used to investigate amino acid mismatches reported as high-risk factors in hematopoietic stem cell transplantation.

This research used the resources of the Argonne Leadership Computing Facility, and was supported by the NIH, the University of Chicago Comprehensive Cancer Center and the DOE Office of Biological and Environmental Research.

References: Binkowski TA, Marino SR, Joachimiak A (2012) Predicting HLA Class I Non-Permissive Amino Acid Residues Substitutions. PLoS ONE 7(8): e41710.