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The | ==Crystal Structure of ILNAMITKI peptide bound to HLA-A2== | ||
<StructureSection load='6pte' size='340' side='right'caption='[[6pte]], [[Resolution|resolution]] 1.90Å' scene=''> | |||
== Structural highlights == | |||
<table><tr><td colspan='2'>[[6pte]] is a 12 chain structure with sequence from [http://en.wikipedia.org/wiki/Human Human]. Full crystallographic information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=6PTE OCA]. For a <b>guided tour on the structure components</b> use [http://oca.weizmann.ac.il/oca-docs/fgij/fg.htm?mol=6PTE FirstGlance]. <br> | |||
</td></tr><tr id='ligand'><td class="sblockLbl"><b>[[Ligand|Ligands:]]</b></td><td class="sblockDat"><scene name='pdbligand=GOL:GLYCEROL'>GOL</scene>, <scene name='pdbligand=NA:SODIUM+ION'>NA</scene></td></tr> | |||
<tr id='related'><td class="sblockLbl"><b>[[Related_structure|Related:]]</b></td><td class="sblockDat">[[6opd|6opd]], [[6ptb|6ptb]]</td></tr> | |||
<tr id='gene'><td class="sblockLbl"><b>[[Gene|Gene:]]</b></td><td class="sblockDat">HLA-A, HLAA ([http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?mode=Info&srchmode=5&id=9606 HUMAN]), B2M, CDABP0092, HDCMA22P ([http://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?mode=Info&srchmode=5&id=9606 HUMAN])</td></tr> | |||
<tr id='resources'><td class="sblockLbl"><b>Resources:</b></td><td class="sblockDat"><span class='plainlinks'>[http://oca.weizmann.ac.il/oca-docs/fgij/fg.htm?mol=6pte FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=6pte OCA], [http://pdbe.org/6pte PDBe], [http://www.rcsb.org/pdb/explore.do?structureId=6pte RCSB], [http://www.ebi.ac.uk/pdbsum/6pte PDBsum], [http://prosat.h-its.org/prosat/prosatexe?pdbcode=6pte ProSAT]</span></td></tr> | |||
</table> | |||
== Disease == | |||
[[http://www.uniprot.org/uniprot/B2MG_HUMAN B2MG_HUMAN]] Defects in B2M are the cause of hypercatabolic hypoproteinemia (HYCATHYP) [MIM:[http://omim.org/entry/241600 241600]]. Affected individuals show marked reduction in serum concentrations of immunoglobulin and albumin, probably due to rapid degradation.<ref>PMID:16549777</ref> Note=Beta-2-microglobulin may adopt the fibrillar configuration of amyloid in certain pathologic states. The capacity to assemble into amyloid fibrils is concentration dependent. Persistently high beta(2)-microglobulin serum levels lead to amyloidosis in patients on long-term hemodialysis.<ref>PMID:3532124</ref> <ref>PMID:1336137</ref> <ref>PMID:7554280</ref> <ref>PMID:4586824</ref> <ref>PMID:8084451</ref> <ref>PMID:12119416</ref> <ref>PMID:12796775</ref> <ref>PMID:16901902</ref> <ref>PMID:16491088</ref> <ref>PMID:17646174</ref> <ref>PMID:18835253</ref> <ref>PMID:18395224</ref> <ref>PMID:19284997</ref> | |||
== Function == | |||
[[http://www.uniprot.org/uniprot/1A02_HUMAN 1A02_HUMAN]] Involved in the presentation of foreign antigens to the immune system. [[http://www.uniprot.org/uniprot/HAUS3_HUMAN HAUS3_HUMAN]] Contributes to mitotic spindle assembly, maintenance of centrosome integrity and completion of cytokinesis as part of the HAUS augmin-like complex.<ref>PMID:19369198</ref> <ref>PMID:19427217</ref> [[http://www.uniprot.org/uniprot/B2MG_HUMAN B2MG_HUMAN]] Component of the class I major histocompatibility complex (MHC). Involved in the presentation of peptide antigens to the immune system. | |||
<div style="background-color:#fffaf0;"> | |||
== Publication Abstract from PubMed == | |||
The development of immunological therapies that incorporate peptide antigens presented to T cells by MHC proteins is a long sought-after goal, particularly for cancer, where mutated neoantigens are being explored as personalized cancer vaccines. Although neoantigens can be identified through sequencing, bioinformatics and mass spectrometry, identifying those which are immunogenic and able to promote tumor rejection remains a significant challenge. Here we examined the potential of high-resolution structural modeling followed by energetic scoring of structural features for predicting neoantigen immunogenicity. After developing a strategy to rapidly and accurately model nonameric peptides bound to the common class I MHC protein HLA-A2, we trained a neural network on structural features that influence T cell receptor (TCR) and peptide binding energies. The resulting structurally-parameterized neural network outperformed methods that do not incorporate explicit structural or energetic properties in predicting CD8(+) T cell responses of HLA-A2 presented nonameric peptides, while also providing insight into the underlying structural and biophysical mechanisms governing immunogenicity. Our proof-of-concept study demonstrates the potential for structure-based immunogenicity predictions in the development of personalized peptide-based vaccines. | |||
Structure Based Prediction of Neoantigen Immunogenicity.,Riley TP, Keller GLJ, Smith AR, Davancaze LM, Arbuiso AG, Devlin JR, Baker BM Front Immunol. 2019 Aug 28;10:2047. doi: 10.3389/fimmu.2019.02047. eCollection, 2019. PMID:31555277<ref>PMID:31555277</ref> | |||
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.<br> | |||
</div> | |||
<div class="pdbe-citations 6pte" style="background-color:#fffaf0;"></div> | |||
[[Category: | == References == | ||
[[Category: | <references/> | ||
__TOC__ | |||
</StructureSection> | |||
[[Category: Human]] | |||
[[Category: Large Structures]] | |||
[[Category: Arbuiso, A]] | [[Category: Arbuiso, A]] | ||
[[Category: Baker, B M]] | |||
[[Category: Keller, G L.J]] | |||
[[Category: Smith, A R]] | |||
[[Category: Hla a2]] | |||
[[Category: Immune system]] | |||
[[Category: Immune system complex]] | |||
[[Category: Mhc class i]] | |||
[[Category: Neoantigen]] |
Revision as of 09:19, 10 October 2019
Crystal Structure of ILNAMITKI peptide bound to HLA-A2Crystal Structure of ILNAMITKI peptide bound to HLA-A2
Structural highlights
Disease[B2MG_HUMAN] Defects in B2M are the cause of hypercatabolic hypoproteinemia (HYCATHYP) [MIM:241600]. Affected individuals show marked reduction in serum concentrations of immunoglobulin and albumin, probably due to rapid degradation.[1] Note=Beta-2-microglobulin may adopt the fibrillar configuration of amyloid in certain pathologic states. The capacity to assemble into amyloid fibrils is concentration dependent. Persistently high beta(2)-microglobulin serum levels lead to amyloidosis in patients on long-term hemodialysis.[2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] Function[1A02_HUMAN] Involved in the presentation of foreign antigens to the immune system. [HAUS3_HUMAN] Contributes to mitotic spindle assembly, maintenance of centrosome integrity and completion of cytokinesis as part of the HAUS augmin-like complex.[15] [16] [B2MG_HUMAN] Component of the class I major histocompatibility complex (MHC). Involved in the presentation of peptide antigens to the immune system. Publication Abstract from PubMedThe development of immunological therapies that incorporate peptide antigens presented to T cells by MHC proteins is a long sought-after goal, particularly for cancer, where mutated neoantigens are being explored as personalized cancer vaccines. Although neoantigens can be identified through sequencing, bioinformatics and mass spectrometry, identifying those which are immunogenic and able to promote tumor rejection remains a significant challenge. Here we examined the potential of high-resolution structural modeling followed by energetic scoring of structural features for predicting neoantigen immunogenicity. After developing a strategy to rapidly and accurately model nonameric peptides bound to the common class I MHC protein HLA-A2, we trained a neural network on structural features that influence T cell receptor (TCR) and peptide binding energies. The resulting structurally-parameterized neural network outperformed methods that do not incorporate explicit structural or energetic properties in predicting CD8(+) T cell responses of HLA-A2 presented nonameric peptides, while also providing insight into the underlying structural and biophysical mechanisms governing immunogenicity. Our proof-of-concept study demonstrates the potential for structure-based immunogenicity predictions in the development of personalized peptide-based vaccines. Structure Based Prediction of Neoantigen Immunogenicity.,Riley TP, Keller GLJ, Smith AR, Davancaze LM, Arbuiso AG, Devlin JR, Baker BM Front Immunol. 2019 Aug 28;10:2047. doi: 10.3389/fimmu.2019.02047. eCollection, 2019. PMID:31555277[17] From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine. References
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