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PDBsum entry 4l3e
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Immune system
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PDB id
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4l3e
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Contents |
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275 a.a.
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100 a.a.
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199 a.a.
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242 a.a.
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References listed in PDB file
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Key reference
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Title
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Computational design of the affinity and specificity of a therapeutic t cell receptor.
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Authors
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B.G.Pierce,
L.M.Hellman,
M.Hossain,
N.K.Singh,
C.W.Vander kooi,
Z.Weng,
B.M.Baker.
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Ref.
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Plos Comput Biol, 2014,
10,
e1003478.
[DOI no: ]
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PubMed id
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Abstract
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T cell receptors (TCRs) are key to antigen-specific immunity and are
increasingly being explored as therapeutics, most visibly in cancer
immunotherapy. As TCRs typically possess only low-to-moderate affinity for their
peptide/MHC (pMHC) ligands, there is a recognized need to develop
affinity-enhanced TCR variants. Previous in vitro engineering efforts have
yielded remarkable improvements in TCR affinity, yet concerns exist about the
maintenance of peptide specificity and the biological impacts of ultra-high
affinity. As opposed to in vitro engineering, computational design can directly
address these issues, in theory permitting the rational control of peptide
specificity together with relatively controlled increments in affinity. Here we
explored the efficacy of computational design with the clinically relevant TCR
DMF5, which recognizes nonameric and decameric epitopes from the
melanoma-associated Melan-A/MART-1 protein presented by the class I MHC HLA-A2.
We tested multiple mutations selected by flexible and rigid modeling protocols,
assessed impacts on affinity and specificity, and utilized the data to examine
and improve algorithmic performance. We identified multiple mutations that
improved binding affinity, and characterized the structure, affinity, and
binding kinetics of a previously reported double mutant that exhibits an
impressive 400-fold affinity improvement for the decameric pMHC ligand without
detectable binding to non-cognate ligands. The structure of this high affinity
mutant indicated very little conformational consequences and emphasized the high
fidelity of our modeling procedure. Overall, our work showcases the capability
of computational design to generate TCRs with improved pMHC affinities while
explicitly accounting for peptide specificity, as well as its potential for
generating TCRs with customized antigen targeting capabilities.
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