6vga
From Proteopedia
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| - | '''Unreleased structure''' | ||
| - | + | ==De novo designed Rossmann fold protein ROS2_835== | |
| + | <StructureSection load='6vga' size='340' side='right'caption='[[6vga]]' scene=''> | ||
| + | == Structural highlights == | ||
| + | <table><tr><td colspan='2'>[[6vga]] is a 1 chain structure with sequence from [https://en.wikipedia.org/wiki/Synthetic_construct Synthetic construct]. Full experimental information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=6VGA OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=6VGA FirstGlance]. <br> | ||
| + | </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=6vga FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=6vga OCA], [https://pdbe.org/6vga PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=6vga RCSB], [https://www.ebi.ac.uk/pdbsum/6vga PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=6vga ProSAT]</span></td></tr> | ||
| + | </table> | ||
| + | <div style="background-color:#fffaf0;"> | ||
| + | == Publication Abstract from PubMed == | ||
| + | Naturally occurring proteins vary the precise geometries of structural elements to create distinct shapes optimal for function. We present a computational design method, loop-helix-loop unit combinatorial sampling (LUCS), that mimics nature's ability to create families of proteins with the same overall fold but precisely tunable geometries. Through near-exhaustive sampling of loop-helix-loop elements, LUCS generates highly diverse geometries encompassing those found in nature but also surpassing known structure space. Biophysical characterization showed that 17 (38%) of 45 tested LUCS designs encompassing two different structural topologies were well folded, including 16 with designed non-native geometries. Four experimentally solved structures closely matched the designs. LUCS greatly expands the designable structure space and offers a new paradigm for designing proteins with tunable geometries that may be customizable for novel functions. | ||
| - | + | Expanding the space of protein geometries by computational design of de novo fold families.,Pan X, Thompson MC, Zhang Y, Liu L, Fraser JS, Kelly MJS, Kortemme T Science. 2020 Aug 28;369(6507):1132-1136. doi: 10.1126/science.abc0881. PMID:32855341<ref>PMID:32855341</ref> | |
| - | + | From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.<br> | |
| - | [[Category: | + | </div> |
| + | <div class="pdbe-citations 6vga" style="background-color:#fffaf0;"></div> | ||
| + | == References == | ||
| + | <references/> | ||
| + | __TOC__ | ||
| + | </StructureSection> | ||
| + | [[Category: Large Structures]] | ||
| + | [[Category: Synthetic construct]] | ||
| + | [[Category: Kelly M]] | ||
| + | [[Category: Kortemme T]] | ||
| + | [[Category: Pan X]] | ||
| + | [[Category: Zhang Y]] | ||
Current revision
De novo designed Rossmann fold protein ROS2_835
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