8sov: Difference between revisions
m Protected "8sov" [edit=sysop:move=sysop] |
No edit summary |
||
| (3 intermediate revisions by the same user not shown) | |||
| Line 1: | Line 1: | ||
==Proteinase K Multiconformer Model at 353K== | |||
<StructureSection load='8sov' size='340' side='right'caption='[[8sov]], [[Resolution|resolution]] 1.29Å' scene=''> | |||
== Structural highlights == | |||
<table><tr><td colspan='2'>[[8sov]] is a 2 chain structure with sequence from [https://en.wikipedia.org/wiki/Parengyodontium_album Parengyodontium album] 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=8SOV OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=8SOV 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]] 1.291Å</td></tr> | |||
<tr id='ligand'><td class="sblockLbl"><b>[[Ligand|Ligands:]]</b></td><td class="sblockDat" id="ligandDat"><scene name='pdbligand=CA:CALCIUM+ION'>CA</scene>, <scene name='pdbligand=SO4:SULFATE+ION'>SO4</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=8sov FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=8sov OCA], [https://pdbe.org/8sov PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=8sov RCSB], [https://www.ebi.ac.uk/pdbsum/8sov PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=8sov ProSAT]</span></td></tr> | |||
</table> | |||
== Function == | |||
[https://www.uniprot.org/uniprot/PRTK_PARAQ PRTK_PARAQ] Hydrolyzes keratin at aromatic and hydrophobic residues. | |||
<div style="background-color:#fffaf0;"> | |||
== Publication Abstract from PubMed == | |||
Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363 K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca(2+) binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships. | |||
Refinement of multiconformer ensemble models from multi-temperature X-ray diffraction data.,Du S, Wankowicz SA, Yabukarski F, Doukov T, Herschlag D, Fraser JS Methods Enzymol. 2023;688:223-254. doi: 10.1016/bs.mie.2023.06.009. Epub 2023 Jul , 27. PMID:37748828<ref>PMID:37748828</ref> | |||
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.<br> | |||
[[Category: | </div> | ||
<div class="pdbe-citations 8sov" style="background-color:#fffaf0;"></div> | |||
==See Also== | |||
*[[Proteinase 3D structures|Proteinase 3D structures]] | |||
== References == | |||
<references/> | |||
__TOC__ | |||
</StructureSection> | |||
[[Category: Large Structures]] | |||
[[Category: Parengyodontium album]] | |||
[[Category: Synthetic construct]] | |||
[[Category: Doukov T]] | |||
[[Category: Du S]] | |||
[[Category: Fraser JS]] | |||
[[Category: Herschlag D]] | |||
[[Category: Wankowicz S]] | |||
[[Category: Yabukarski F]] | |||
Latest revision as of 15:31, 23 October 2024
Proteinase K Multiconformer Model at 353KProteinase K Multiconformer Model at 353K
Structural highlights
FunctionPRTK_PARAQ Hydrolyzes keratin at aromatic and hydrophobic residues. Publication Abstract from PubMedConformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363 K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca(2+) binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships. Refinement of multiconformer ensemble models from multi-temperature X-ray diffraction data.,Du S, Wankowicz SA, Yabukarski F, Doukov T, Herschlag D, Fraser JS Methods Enzymol. 2023;688:223-254. doi: 10.1016/bs.mie.2023.06.009. Epub 2023 Jul , 27. PMID:37748828[1] From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine. See AlsoReferences
|
| ||||||||||||||||||