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| Title | Automated simulation-based membrane protein refinement into cryo-EM data. |
|---|---|
| Journal, issue, pages | Biophys J, Vol. 122, Issue 13, Page 2773-2781, Year 2023 |
| Publish date | Jul 11, 2023 |
 Authors | Linnea Yvonnesdotter / Urška Rovšnik / Christian Blau / Marie Lycksell / Rebecca Joy Howard / Erik Lindahl /  |
| 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 ...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. |
 External links | Biophys J / PubMed:37277992 / PubMed Central |
| Methods | EM (single particle) |
| Resolution | 3.0 Å |
| Structure data | EMDB-15903, PDB-8b7v: |
| Source |
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 Keywords |  MEMBRANE PROTEIN / maltoporin / density fit / automated refinement / cryo-em |
