6JTP

Crystal structure of HLA-C08 in complex with a tumor mut9m peptide


Experimental Data Snapshot

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.90 Å
  • R-Value Free: 0.283 
  • R-Value Work: 0.240 
  • R-Value Observed: 0.242 

wwPDB Validation   3D Report Full Report


This is version 1.2 of the entry. See complete history


Literature

Immune-based mutation classification enables neoantigen prioritization and immune feature discovery in cancer immunotherapy.

Bai, P.Li, Y.Zhou, Q.Xia, J.Wei, P.C.Deng, H.Wu, M.Chan, S.K.Kappler, J.W.Zhou, Y.Tran, E.Marrack, P.Yin, L.

(2021) Oncoimmunology 10: 1868130-1868130

  • DOI: 10.1080/2162402X.2020.1868130
  • Primary Citation of Related Structures:  
    6JQ2, 6JQ3, 6JTP, 6JTN

  • PubMed Abstract: 
  • Genetic mutations lead to the production of mutated proteins from which peptides are presented to T cells as cancer neoantigens. Evidence suggests that T cells that target neoantigens are the main mediators of effective cancer immunotherapies. Although a ...

    Genetic mutations lead to the production of mutated proteins from which peptides are presented to T cells as cancer neoantigens. Evidence suggests that T cells that target neoantigens are the main mediators of effective cancer immunotherapies. Although algorithms have been used to predict neoantigens, only a minority are immunogenic. The factors that influence neoantigen immunogenicity are not completely understood. Here, we classified human neoantigen/neopeptide data into three categories based on their TCR-pMHC binding events. We observed a conservative mutant orientation of the anchor residue from immunogenic neoantigens which we termed the "NP" rule. By integrating this rule with an existing prediction algorithm, we found improved performance in neoantigen prioritization. To better understand this rule, we solved several neoantigen/MHC structures. These structures showed that neoantigens that follow this rule not only increase peptide-MHC binding affinity but also create new TCR-binding features. These molecular insights highlight the value of immune-based classification in neoantigen studies and may enable the design of more effective cancer immunotherapies.


    Organizational Affiliation

    State Key Laboratory of Virology, Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Wuhan University, Wuhan, China.



Macromolecules
Find similar proteins by:  (by identity cutoff)  |  Structure
Entity ID: 1
MoleculeChainsSequence LengthOrganismDetailsImage
HLA class I antigen, Cw8.2 alpha chain A273Homo sapiensMutation(s): 0 
Gene Names: HLA-CwHLA-C
Find proteins for C1K0Y1 (Homo sapiens)
Explore C1K0Y1 
Go to UniProtKB:  C1K0Y1
Protein Feature View
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  • Reference Sequence
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Entity ID: 2
MoleculeChainsSequence LengthOrganismDetailsImage
Beta-2-microglobulin B98Homo sapiensMutation(s): 0 
Gene Names: B2MCDABP0092HDCMA22P
Find proteins for P61769 (Homo sapiens)
Explore P61769 
Go to UniProtKB:  P61769
NIH Common Fund Data Resources
PHAROS:  P61769
Protein Feature View
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  • Reference Sequence
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Entity ID: 3
MoleculeChainsSequence LengthOrganismDetailsImage
9-mer peptide C9Homo sapiensMutation(s): 0 
Gene Names: KRASKRAS2RASK2
EC: 3.6.5.2
Find proteins for P01116 (Homo sapiens)
Explore P01116 
Go to UniProtKB:  P01116
NIH Common Fund Data Resources
PHAROS:  P01116
Protein Feature View
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  • Reference Sequence
Experimental Data & Validation

Experimental Data

  • Method: X-RAY DIFFRACTION
  • Resolution: 1.90 Å
  • R-Value Free: 0.283 
  • R-Value Work: 0.240 
  • R-Value Observed: 0.242 
  • Space Group: P 21 21 21
Unit Cell:
Length ( Å )Angle ( ˚ )
a = 68.28α = 90
b = 75.92β = 90
c = 78.03γ = 90
Software Package:
Software NamePurpose
PHENIXrefinement
iMOSFLMdata reduction
Aimlessdata scaling
PHASERphasing

Structure Validation

View Full Validation Report



Entry History 

Deposition Data

Revision History 

  • Version 1.0: 2020-04-15
    Type: Initial release
  • Version 1.1: 2021-02-03
    Changes: Database references
  • Version 1.2: 2021-02-17
    Changes: Database references