8b7v: Difference between revisions

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== Structural highlights ==
== Structural highlights ==
<table><tr><td colspan='2'>[[8b7v]] is a 3 chain structure with sequence from [https://en.wikipedia.org/wiki/Escherichia_coli Escherichia coli]. Full crystallographic information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=8B7V OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=8B7V FirstGlance]. <br>
<table><tr><td colspan='2'>[[8b7v]] is a 3 chain structure with sequence from [https://en.wikipedia.org/wiki/Escherichia_coli Escherichia coli]. Full crystallographic information is available from [http://oca.weizmann.ac.il/oca-bin/ocashort?id=8B7V OCA]. For a <b>guided tour on the structure components</b> use [https://proteopedia.org/fgij/fg.htm?mol=8B7V 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=8b7v FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=8b7v OCA], [https://pdbe.org/8b7v PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=8b7v RCSB], [https://www.ebi.ac.uk/pdbsum/8b7v PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=8b7v ProSAT]</span></td></tr>
</td></tr><tr id='method'><td class="sblockLbl"><b>[[Empirical_models|Method:]]</b></td><td class="sblockDat" id="methodDat">Electron Microscopy, [[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=8b7v FirstGlance], [http://oca.weizmann.ac.il/oca-bin/ocaids?id=8b7v OCA], [https://pdbe.org/8b7v PDBe], [https://www.rcsb.org/pdb/explore.do?structureId=8b7v RCSB], [https://www.ebi.ac.uk/pdbsum/8b7v PDBsum], [https://prosat.h-its.org/prosat/prosatexe?pdbcode=8b7v ProSAT]</span></td></tr>
</table>
</table>
== Function ==
== Function ==

Latest revision as of 15:51, 26 July 2023

Automated simulation-based refinement of maltoporin into a cryo-EM densityAutomated simulation-based refinement of maltoporin into a cryo-EM density

Structural highlights

8b7v is a 3 chain structure with sequence from Escherichia coli. Full crystallographic information is available from OCA. For a guided tour on the structure components use FirstGlance.
Method:Electron Microscopy, Resolution 3Å
Resources:FirstGlance, OCA, PDBe, RCSB, PDBsum, ProSAT

Function

A0A2X5NX10_ECOLX Involved in the transport of maltose and maltodextrins.[HAMAP-Rule:MF_01301]

Publication Abstract from PubMed

The resolution revolution has increasingly enabled single-particle cryogenic electron microscopy (cryo-EM) reconstructions of previously inaccessible systems, including membrane proteins-a category that constitutes a disproportionate share of drug targets. We present a protocol for using density-guided molecular dynamics simulations to automatically refine atomistic models into membrane protein cryo-EM maps. Using adaptive force density-guided simulations as implemented in the GROMACS molecular dynamics package, we show how automated model refinement of a membrane protein is achieved without the need to manually tune the fitting force ad hoc. We also present selection criteria to choose the best-fit model that balances stereochemistry and goodness of fit. The proposed protocol was used to refine models into a new cryo-EM density of the membrane protein maltoporin, either in a lipid bilayer or detergent micelle, and we found that results do not substantially differ from fitting in solution. Fitted structures satisfied classical model-quality metrics and improved the quality and the model-to-map correlation of the x-ray starting structure. Additionally, the density-guided fitting in combination with generalized orientation-dependent all-atom potential was used to correct the pixel-size estimation of the experimental cryo-EM density map. This work demonstrates the applicability of a straightforward automated approach to fitting membrane protein cryo-EM densities. Such computational approaches promise to facilitate rapid refinement of proteins under different conditions or with various ligands present, including targets in the highly relevant superfamily of membrane proteins.

Automated simulation-based membrane protein refinement into cryo-EM data.,Yvonnesdotter L, Rovsnik U, Blau C, Lycksell M, Howard RJ, Lindahl E Biophys J. 2023 Jun 5:S0006-3495(23)00367-3. doi: 10.1016/j.bpj.2023.05.033. PMID:37277992[1]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

References

  1. Yvonnesdotter L, Rovšnik U, Blau C, Lycksell M, Howard RJ, Lindahl E. Automated simulation-based membrane protein refinement into cryo-EM data. Biophys J. 2023 Jun 5:S0006-3495(23)00367-3. PMID:37277992 doi:10.1016/j.bpj.2023.05.033

8b7v, resolution 3.00Å

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OCA