View source for 7xad


==Crystal strucutre of PD-L1 and DBL2_02 designed protein binder==
<StructureSection load='7xad' size='340' side='right'caption='[[7xad]], [[Resolution|resolution]] 3.00&Aring;' scene=''>
== Structural highlights ==
<table><tr><td colspan='2'>[[7xad]] is a 8 chain structure with sequence from [https://en.wikipedia.org/wiki/Homo_sapiens Homo sapiens] and [https://en.wikipedia.org/wiki/Chemical_production_metagenome Chemical production metagenome]. Full crystallographic information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=7XAD OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=7XAD FirstGlance]. <br>
</td></tr><tr id='method'><td class="sblockLbl"><b>[[Empirical_models|Method:]]</b></td><td class="sblockDat" id="methodDat">X-ray diffraction, [[Resolution|Resolution]] 3&#8491;</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=7xad FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=7xad OCA], [https://pdbe.org/7xad PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=7xad RCSB], [https://www.ebi.ac.uk/pdbsum/7xad PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=7xad ProSAT]</span></td></tr>
</table>
== Function ==
[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&reg;/PubMed&reg;, a database of the U.S. National Library of Medicine.<br>
</div>
<div class="pdbe-citations 7xad" style="background-color:#fffaf0;"></div>
== References ==
<references/>
__TOC__
</StructureSection>
[[Category: Chemical production metagenome]]
[[Category: Homo sapiens]]
[[Category: Large Structures]]
[[Category: Chai Y]]
[[Category: Gao GF]]
[[Category: Han P]]
[[Category: Liu KF]]
[[Category: Pacesa M]]
[[Category: Tan SG]]
[[Category: Xu ZP]]