8D5K image
Entry Detail
PDB ID:
8D5K
Keywords:
Title:
The complex of Pre-mRNA-Processing Factor 19 (Prpf19) peptide KYLQVASHV Presented by H2-Kd
Biological Source:
Source Organism:
PDB Version:
Deposition Date:
2022-06-05
Release Date:
2022-07-06
Method Details:
Experimental Method:
Resolution:
2.07 Å
R-Value Free:
0.23
R-Value Work:
0.20
Space Group:
C 1 2 1
Macromolecular Entities
Polymer Type:polypeptide(L)
Description:H-2 class I histocompatibility antigen, K-D alpha chain
Chain IDs:A
Chain Length:275
Number of Molecules:1
Biological Source:Mus musculus
Polymer Type:polypeptide(L)
Description:Beta-2-microglobulin
Chain IDs:B
Chain Length:100
Number of Molecules:1
Biological Source:Mus musculus
Polymer Type:polypeptide(L)
Description:Pre-mRNA-processing factor 19
Chain IDs:C
Chain Length:9
Number of Molecules:1
Biological Source:Mus musculus
Primary Citation
Structural and physical features that distinguish tumor-controlling from inactive cancer neoepitopes.
Proc.Natl.Acad.Sci.USA 120 e2312057120 e2312057120 (2023)
PMID: 38085776 DOI: 10.1073/pnas.2312057120

Abstact

Neoepitopes arising from amino acid substitutions due to single nucleotide polymorphisms are targets of T cell immune responses to cancer and are of significant interest in the development of cancer vaccines. However, understanding the characteristics of rare protective neoepitopes that truly control tumor growth has been a challenge, due to their scarcity as well as the challenge of verifying true, neoepitope-dependent tumor control in humans. Taking advantage of recent work in mouse models that circumvented these challenges, here, we compared the structural and physical properties of neoepitopes that range from fully protective to immunologically inactive. As neoepitopes are derived from self-peptides that can induce immune tolerance, we studied not only how the various neoepitopes differ from each other but also from their wild-type counterparts. We identified multiple features associated with protection, including features that describe how neoepitopes differ from self as well as features associated with recognition by diverse T cell receptor repertoires. We demonstrate both the promise and limitations of neoepitope structural analysis and predictive modeling and illustrate important aspects that can be incorporated into neoepitope prediction pipelines.

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Primary Citation of related structures