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

Experimental Data Snapshot

  • Resolution: 3.00 Å
  • Aggregation State: PARTICLE 
  • Reconstruction Method: SINGLE PARTICLE 

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Automated simulation-based membrane protein refinement into cryo-EM data.

Yvonnesdotter, L.Rovsnik, U.Blau, C.Lycksell, M.Howard, R.J.Lindahl, E.

(2023) Biophys J 122: 2773-2781

  • DOI: https://doi.org/10.1016/j.bpj.2023.05.033
  • Primary Citation of Related Structures:  

  • PubMed Abstract: 

    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.

  • Organizational Affiliation

    Science for Life Laboratory & Swedish e-Science Research Center, Department of Applied Physics, KTH Royal Institute of Technology, Solna, Sweden.

Find similar proteins by:  (by identity cutoff)  |  3D Structure
Entity ID: 1
MoleculeChains Sequence LengthOrganismDetailsImage
A, B, C
421Escherichia coliMutation(s): 0 
Membrane Entity: Yes 
Find proteins for P02943 (Escherichia coli (strain K12))
Explore P02943 
Go to UniProtKB:  P02943
Entity Groups  
Sequence Clusters30% Identity50% Identity70% Identity90% Identity95% Identity100% Identity
UniProt GroupP02943
Sequence Annotations
  • Reference Sequence
Experimental Data & Validation

Experimental Data

  • Resolution: 3.00 Å
  • Aggregation State: PARTICLE 
  • Reconstruction Method: SINGLE PARTICLE 

Structure Validation

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Entry History & Funding Information

Deposition Data

Funding OrganizationLocationGrant Number
Swedish Research CouncilSweden2019-02433
Knut and Alice Wallenberg FoundationSweden1484505

Revision History  (Full details and data files)

  • Version 1.0: 2023-06-21
    Type: Initial release
  • Version 1.1: 2023-07-26
    Changes: Database references