bims-lances Biomed News
on Landscapes from Cryo-EM and Simulations
Issue of 2024–10–13
one paper selected by
James M. Krieger, National Centre for Biotechnology
  1. Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks.
  1. bioRxiv. 2024 Sep 27. pii: 2024.09.27.615511. [Epub ahead of print]
    Building molecular model series from heterogeneous CryoEM structures using Gaussian mixture models and deep neural networks.
    Muyuan Chen.
      Cryogenic electron microscopy (CryoEM) produces structures of macromolecules at near-atomic resolution. However, building molecular models with good stereochemical geometry from those structures can be challenging and time-consuming, especially when many structures are obtained from datasets with conformational heterogeneity. Here we present a model refinement protocol that automatically generates series of molecular models from CryoEM datasets, which describe the dynamics of the macromolecular system and have near-perfect geometry scores.
    DOI:  https://doi.org/10.1101/2024.09.27.615511
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