Computational models of amorphous ice for accurate simulation of cryo-EM images of biological samples.

ABSTRACT: Simulations of cryo-electron microscopy (cryo-EM) images of biological samples can be used to produce test datasets to support the development of instrumentation, methods, and software, as well as to assess data acquisition and analysis strategies. To be useful, these simulations need to be based on physically realistic models which include large volumes of amorphous ice. The gold standard model for EM image simulation is a physical atom-based ice model produced using molecular dynamics simulations. Although practical for small sample volumes; for simulation of cryo-EM data from large sample volumes, this can be too computationally expensive. We have evaluated a Gaussian Random Field (GRF) ice model which is shown to be more computationally efficient for large sample volumes. The simulated

SUBMITTER: Parkhurst JM 

PROVIDER: S-EPMC10730944 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature