7xyq
From Proteopedia
(Difference between revisions)
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== Structural highlights == | == Structural highlights == | ||
<table><tr><td colspan='2'>[[7xyq]] is a 2 chain structure with sequence from [https://en.wikipedia.org/wiki/Homo_sapiens Homo sapiens] and [https://en.wikipedia.org/wiki/Synthetic_construct Synthetic construct]. Full crystallographic information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=7XYQ OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=7XYQ FirstGlance]. <br> | <table><tr><td colspan='2'>[[7xyq]] is a 2 chain structure with sequence from [https://en.wikipedia.org/wiki/Homo_sapiens Homo sapiens] and [https://en.wikipedia.org/wiki/Synthetic_construct Synthetic construct]. Full crystallographic information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=7XYQ OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=7XYQ FirstGlance]. <br> | ||
- | </td></tr><tr id='ligand'><td class="sblockLbl"><b>[[Ligand|Ligands:]]</b></td><td class="sblockDat" id="ligandDat"><scene name='pdbligand=ARG:ARGININE'>ARG</scene></td></tr> | + | </td></tr><tr id='method'><td class="sblockLbl"><b>[[Empirical_models|Method:]]</b></td><td class="sblockDat" id="methodDat">X-ray diffraction, [[Resolution|Resolution]] 2.85Å</td></tr> |
+ | <tr id='ligand'><td class="sblockLbl"><b>[[Ligand|Ligands:]]</b></td><td class="sblockDat" id="ligandDat"><scene name='pdbligand=ARG:ARGININE'>ARG</scene></td></tr> | ||
<tr id='resources'><td class="sblockLbl"><b>Resources:</b></td><td class="sblockDat"><span class='plainlinks'>[https://proteopedia.org/fgij/fg.htm?mol=7xyq FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=7xyq OCA], [https://pdbe.org/7xyq PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=7xyq RCSB], [https://www.ebi.ac.uk/pdbsum/7xyq PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=7xyq ProSAT]</span></td></tr> | <tr id='resources'><td class="sblockLbl"><b>Resources:</b></td><td class="sblockDat"><span class='plainlinks'>[https://proteopedia.org/fgij/fg.htm?mol=7xyq FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=7xyq OCA], [https://pdbe.org/7xyq PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=7xyq RCSB], [https://www.ebi.ac.uk/pdbsum/7xyq PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=7xyq ProSAT]</span></td></tr> | ||
</table> | </table> | ||
== Function == | == Function == | ||
- | [https://www.uniprot.org/uniprot/ | + | [https://www.uniprot.org/uniprot/PD1L1_HUMAN PD1L1_HUMAN] Involved in the costimulatory signal, essential for T-cell proliferation and production of IL10 and IFNG, in an IL2-dependent and a PDCD1-independent manner. Interaction with PDCD1 inhibits T-cell proliferation and cytokine production.<ref>PMID:10581077</ref> <ref>PMID:11015443</ref> |
+ | <div style="background-color:#fffaf0;"> | ||
+ | == Publication Abstract from PubMed == | ||
+ | Physical interactions between proteins are essential for most biological processes governing life(1). However, the molecular determinants of such interactions have been challenging to understand, even as genomic, proteomic and structural data increase. This knowledge gap has been a major obstacle for the comprehensive understanding of cellular protein-protein interaction networks and for the de novo design of protein binders that are crucial for synthetic biology and translational applications(2-9). Here we use a geometric deep-learning framework operating on protein surfaces that generates fingerprints to describe geometric and chemical features that are critical to drive protein-protein interactions(10). We hypothesized that these fingerprints capture the key aspects of molecular recognition that represent a new paradigm in the computational design of novel protein interactions. As a proof of principle, we computationally designed several de novo protein binders to engage four protein targets: SARS-CoV-2 spike, PD-1, PD-L1 and CTLA-4. Several designs were experimentally optimized, whereas others were generated purely in silico, reaching nanomolar affinity with structural and mutational characterization showing highly accurate predictions. Overall, our surface-centric approach captures the physical and chemical determinants of molecular recognition, enabling an approach for the de novo design of protein interactions and, more broadly, of artificial proteins with function. | ||
+ | |||
+ | De novo design of protein interactions with learned surface fingerprints.,Gainza P, Wehrle S, Van Hall-Beauvais A, Marchand A, Scheck A, Harteveld Z, Buckley S, Ni D, Tan S, Sverrisson F, Goverde C, Turelli P, Raclot C, Teslenko A, Pacesa M, Rosset S, Georgeon S, Marsden J, Petruzzella A, Liu K, Xu Z, Chai Y, Han P, Gao GF, Oricchio E, Fierz B, Trono D, Stahlberg H, Bronstein M, Correia BE Nature. 2023 May;617(7959):176-184. doi: 10.1038/s41586-023-05993-x. Epub 2023 , Apr 26. PMID:37100904<ref>PMID:37100904</ref> | ||
+ | |||
+ | From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.<br> | ||
+ | </div> | ||
+ | <div class="pdbe-citations 7xyq" style="background-color:#fffaf0;"></div> | ||
+ | == References == | ||
+ | <references/> | ||
__TOC__ | __TOC__ | ||
</StructureSection> | </StructureSection> |
Current revision
Crystal strucutre of PD-L1 and the computationally designed DBL1_03 protein binder
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Categories: Homo sapiens | Large Structures | Synthetic construct | Chai Y | Gao GF | Han P | Liu K | Pacesa M | Tan S | Xu Z