Predicting HLA class I non-permissive amino acid residues substitutions.
Prediction of peptide binding to human leukocyte antigen (HLA) molecules is essential to a wide range of clinical entities from vaccine design to stem cell transplant compatibility. Here we present a new structure-based methodology that applies robust computational tools to model peptide-HLA (p-HLA) binding interactions. The method leverages the structural conservation observed in p-HLA complexes to significantly reduce the search space and calculate the system's binding free energy. This approach is benchmarked against existing p-HLA complexes and the prediction performance is measured against a library of experimentally validated peptides. 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.
Biosciences Division, Argonne National Laboratory, Midwest Center for Structural Genomics, Argonne, Illinois, United States of America.
T Andrew
TA
Binkowski
Susana R
SR
Marino
Andrzej
A
Joachimiak
D000595:Amino Acid Sequence; D019943:Amino Acid Substitution; D000596:Amino Acids / Q000737:chemistry*; D019540:Area Under Curve; D018360:Crystallography, X-Ray / Q000379:methods; D030562:Databases, Protein; D018380:Hematopoietic Stem Cell Transplantation / Q000379:methods; D015395:Histocompatibility Antigens Class I / Q000378:metabolism*; D006801:Humans; D008958:Models, Molecular; D008969:Molecular Sequence Data; D010455:Peptides / Q000737:chemistry; D011485:Protein Binding; D011487:Protein Conformation; D015203:Reproducibility of Results; D012306:Risk; D012307:Risk Factors; D013816:Thermodynamics
D000596:Amino Acids; D015395:Histocompatibility Antigens Class I; D010455:Peptides