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| - | ==Sohair: a designed granulopoietic protein by topological rescaffolding== | + | ==Moevan: a designed granulopoietic protein by topological rescaffolding== | 
| - | <StructureSection load='6y06' size='340' side='right'caption='[[6y06]], [[NMR_Ensembles_of_Models | 14 NMR models]]' scene=''> | + | <StructureSection load='6y06' size='340' side='right'caption='[[6y06]]' scene=''> | 
|  | == Structural highlights == |  | == Structural highlights == | 
| - | <table><tr><td colspan='2'>[[6y06]] is a 1 chain structure with sequence from [http://en.wikipedia.org/wiki/Synthetic_construct_sequences Synthetic constructsequences]. Full experimental information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=6Y06 OCA]. For a <b>guided tour on the structure components</b> use [http://oca.weizmann.ac.il/oca-docs/fgij/fg.htm?mol=6Y06 FirstGlance]. <br> | + | <table><tr><td colspan='2'>[[6y06]] 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=6Y06 OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=6Y06 FirstGlance]. <br> | 
| - | </td></tr><tr id='related'><td class="sblockLbl"><b>[[Related_structure|Related:]]</b></td><td class="sblockDat">[[6y07|6y07]]</td></tr> | + | </td></tr><tr id='method'><td class="sblockLbl"><b>[[Empirical_models|Method:]]</b></td><td class="sblockDat" id="methodDat">Solution NMR</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=6y06 FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=6y06 OCA], [http://pdbe.org/6y06 PDBe], [http://www.rcsb.org/pdb/explore.do?structureId=6y06 RCSB], [http://www.ebi.ac.uk/pdbsum/6y06 PDBsum], [http://prosat.h-its.org/prosat/prosatexe?pdbcode=6y06 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=6y06 FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=6y06 OCA], [https://pdbe.org/6y06 PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=6y06 RCSB], [https://www.ebi.ac.uk/pdbsum/6y06 PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=6y06 ProSAT]</span></td></tr> | 
|  | </table> |  | </table> | 
|  | <div style="background-color:#fffaf0;"> |  | <div style="background-color:#fffaf0;"> | 
|  | == Publication Abstract from PubMed == |  | == Publication Abstract from PubMed == | 
| - | The ability of proteins to adopt multiple conformational states isessential to their function, andelucidating thedetails ofsuch diversity under physiological conditions has been a major challenge. Here we present a generalized method for mapping proteinpopulation landscapes byNMR spectroscopy. Experimental NOESY spectra are directly compared with a set of expectation spectra back-calculated across an arbitrary conformational space. Signal decomposition of theexperimental spectrum then directly yields therelative populations of local conformational microstates. In thisway,averaged descriptions ofconformation can be eliminated.As themethod quantitatively compares experimental andexpectation spectra,it inherently delivers an R factor expressing how well structural modelsexplain the input data.We demonstrate that our method extracts sufficient information from a single 3D NOESY experiment toperform initial model building, refinement, andvalidation,thus offering acomplete de novo structure determination protocol.
 | + | Computational protein design is rapidly becoming more powerful, and improving the accuracy of computational methods would greatly streamline protein engineering by eliminating the need for empirical optimization in the laboratory. In this work, we set out to design novel granulopoietic agents using a rescaffolding strategy with the goal of achieving simpler and more stable proteins. All of the 4 experimentally tested designs were folded, monomeric, and stable, while the 2 determined structures agreed with the design models within less than 2.5 A. Despite the lack of significant topological or sequence similarity to their natural granulopoietic counterpart, 2 designs bound to the granulocyte colony-stimulating factor (G-CSF) receptor and exhibited potent, but delayed, in vitro proliferative activity in a G-CSF-dependent cell line. Interestingly, the designs also induced proliferation and differentiation of primary human hematopoietic stem cells into mature granulocytes, highlighting the utility of our approach to develop highly active therapeutic leads purely based on computational design. | 
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| - | Mapping Local Conformational Landscapes ofProteins in Solution.,ElGamacy M,Riss M,Zhu H,Truffault V,Coles MStructure.2019 Mar 26. pii: S0969-2126(19)30083-8. doi:, 10.1016/j.str.2019.03.005. PMID:30930065<ref>PMID:30930065</ref>
 | + | Design of novel granulopoietic proteins by topological rescaffolding.,Hernandez Alvarez B, Skokowa J, Coles M, Mir P, Nasri M, Maksymenko K, Weidmann L, Rogers KW, Welte K, Lupas AN, Muller P, ElGamacy M PLoS Biol. 2020 Dec 22;18(12):e3000919. doi: 10.1371/journal.pbio.3000919., eCollection 2020 Dec. PMID:33351791<ref>PMID:33351791</ref> | 
|  |  |  |  | 
|  | From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.<br> |  | From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.<br> | 
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|  | </StructureSection> |  | </StructureSection> | 
|  | [[Category: Large Structures]] |  | [[Category: Large Structures]] | 
| - | [[Category: Synthetic construct sequences]] | + | [[Category: Synthetic construct]] | 
| - | [[Category: Coles, M]] | + | [[Category: Coles M]] | 
| - | [[Category: ElGamacy, M]] | + | [[Category: ElGamacy M]] | 
| - | [[Category: De novo protein]]
 | + |  | 
| - | [[Category: Gcsf mimic]]
 | + |  | 
| - | [[Category: Protein design]]
 | + |  | 
| - | [[Category: Receptor modulator]]
 | + |  | 
|  |   Structural highlights 
  Publication Abstract from PubMed Computational protein design is rapidly becoming more powerful, and improving the accuracy of computational methods would greatly streamline protein engineering by eliminating the need for empirical optimization in the laboratory. In this work, we set out to design novel granulopoietic agents using a rescaffolding strategy with the goal of achieving simpler and more stable proteins. All of the 4 experimentally tested designs were folded, monomeric, and stable, while the 2 determined structures agreed with the design models within less than 2.5 A. Despite the lack of significant topological or sequence similarity to their natural granulopoietic counterpart, 2 designs bound to the granulocyte colony-stimulating factor (G-CSF) receptor and exhibited potent, but delayed, in vitro proliferative activity in a G-CSF-dependent cell line. Interestingly, the designs also induced proliferation and differentiation of primary human hematopoietic stem cells into mature granulocytes, highlighting the utility of our approach to develop highly active therapeutic leads purely based on computational design.
 Design of novel granulopoietic proteins by topological rescaffolding.,Hernandez Alvarez B, Skokowa J, Coles M, Mir P, Nasri M, Maksymenko K, Weidmann L, Rogers KW, Welte K, Lupas AN, Muller P, ElGamacy M PLoS Biol. 2020 Dec 22;18(12):e3000919. doi: 10.1371/journal.pbio.3000919., eCollection 2020 Dec. PMID:33351791[1]
 From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.
   References ↑ Hernandez Alvarez B, Skokowa J, Coles M, Mir P, Nasri M, Maksymenko K, Weidmann L, Rogers KW, Welte K, Lupas AN, Muller P, ElGamacy M. Design of novel granulopoietic proteins by topological rescaffolding. PLoS Biol. 2020 Dec 22;18(12):e3000919. doi: 10.1371/journal.pbio.3000919., eCollection 2020 Dec. PMID:33351791 doi:http://dx.doi.org/10.1371/journal.pbio.3000919
 
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