Recognizing amino acid sidechains in a medium resolution cryo-electron density map.

ABSTRACT: Building an accurate atomic structure model of a protein into a cryo-electron microscopy (cryo-EM) map at worse than 3 Å resolution is difficult. To facilitate this task, we devised a method for assigning the amino acid residue sequence to the backbone fragments traced in an input cryo-EM map (EMSequenceFinder). EMSequenceFinder relies on a Bayesian scoring function for ranking 20 standard amino acid residue types at a given backbone position, based on the fit to a density map, map resolution, and secondary structure propensity. The fit to a density is quantified by a convolutional neural network that was trained on ~5.56 million amino acid residue densities extracted from cryo-EM maps at 3-10 Å resolution and corresponding atomic structure models deposited in the Electron Mi

SUBMITTER: Mondal D 

PROVIDER: S-EPMC12247757 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature