Experimental structures of antibody/MHC-I complexes reveal details of epitopes overlooked by computational prediction
L. F. Boyd, J. Jiang, J. Ahmad, K. Natarajan, D. H. Margulies
Abstract
Monoclonal antibodies (mAb) to major histocompatibility complex class I (MHC-I) molecules have proved to be crucial reagents for tissue typing and fundamental studies of immune recognition. To augment our understanding of epitopic sites seen by a set of anti-MHC-I mAb, we determined X-ray crystal structures of four complexes of anti-MHC-I antigen-binding fragments (Fab) bound to peptide/MHC-I/{beta}2m (pMHC-I). An anti-H2-Dd mAb, two anti-MHC-I 3 domain mAb, and an anti-{beta}2-microglobulin ({beta}2m) mAb bind pMHC-I at sites consistent with earlier mutational and functional experiments, and the structures explain allelomorph specificity. Comparison of the experimentally determined structures with computationally derived models using AlphaFold Multimer (AF-M) showed that although predictions of the individual pMHC-I heterodimers were quite acceptable, the computational models failed to properly identify the docking sites of the mAb on pMHC-I. The experimental and predicted structures provide insight into strengths and weaknesses of purely computational approaches and suggest areas that merit additional attention. ONE SENTENCE SUMMARYX-ray structures of anti-MHC-I/MHC-I complexes define epitopes overlooked by computational prediction.
02 /Specification & Classification
Click any tag to browse matching papers- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Cryo-EM and X-ray structures of an anti-MHC-I monoclonal antibody/H2-Kb complex reveal the basis of conformational dependence and allelic specificity
Jiansheng Jiang, Kannan Natarajan, … David H. Margulies·bioRxiv·Sep 16, 2026
- Accurate modeling of peptide-MHC structures with AlphaFold
V. Mikhaylov, A. J. Levine·StructurePeer-reviewed·Feb 1, 2024
- Evaluation of the Ability of AlphaFold to Predict the Three-Dimensional Structures of Antibodies and Epitopes
K. Polonsky, T. Pupko, N. Freund·bioRxiv·Aug 3, 2023
- A Comparison of Antibody-Antigen Complex Sequence-to-Structure Prediction Methods and their Systematic Biases
Katherine Maia McCoy, Margaret E. Ackerman, Gevorg Grigoryan·Protein SciencePeer-reviewed·Aug 21, 2024
- Benchmarking AlphaFold and related deep learning approaches for modeling antibody and TCR antigen recognition
Rui Yin, Shayana Saravanakumar, … Brian G. Pierce·bioRxiv·Jul 6, 2026
- Structure modeling and specificity of peptide-MHC class I interactions using geometric deep learning
Alon Aronson, Tanya Hochner, … Dina Schneidman‐Duhovny·bioRxiv·Dec 15, 2022