James M. Parkhurst , Anna Cavalleri , Maud Dumoux , Mark Basham , Daniel Clare , C. Alistair Siebert , Gwyndaf Evans , James H. Naismith , Angus Kirkland , Jonathan W. Essex
{"title":"Computational models of amorphous ice for accurate simulation of cryo-EM images of biological samples","authors":"James M. Parkhurst , Anna Cavalleri , Maud Dumoux , Mark Basham , Daniel Clare , C. Alistair Siebert , Gwyndaf Evans , James H. Naismith , Angus Kirkland , Jonathan W. Essex","doi":"10.1016/j.ultramic.2023.113882","DOIUrl":null,"url":null,"abstract":"<div><p>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 EM images are compared with the gold standard atom-based ice model approach and shown to be directly comparable. Comparison with experimentally acquired data shows the Gaussian random field ice model produces realistic simulations. The software required has been implemented in the Parakeet software package and the underlying atomic models are available online for use by the wider community.</p></div>","PeriodicalId":23439,"journal":{"name":"Ultramicroscopy","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2023-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0304399123001997/pdfft?md5=41f8dc87b7909c3e15715682352759e0&pid=1-s2.0-S0304399123001997-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ultramicroscopy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304399123001997","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MICROSCOPY","Score":null,"Total":0}
引用次数: 0
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 EM images are compared with the gold standard atom-based ice model approach and shown to be directly comparable. Comparison with experimentally acquired data shows the Gaussian random field ice model produces realistic simulations. The software required has been implemented in the Parakeet software package and the underlying atomic models are available online for use by the wider community.
期刊介绍:
Ultramicroscopy is an established journal that provides a forum for the publication of original research papers, invited reviews and rapid communications. The scope of Ultramicroscopy is to describe advances in instrumentation, methods and theory related to all modes of microscopical imaging, diffraction and spectroscopy in the life and physical sciences.