ModelAngelo: Automated Model Building in Cryo-EM Maps
- URL: http://arxiv.org/abs/2210.00006v1
- Date: Fri, 30 Sep 2022 16:47:45 GMT
- Title: ModelAngelo: Automated Model Building in Cryo-EM Maps
- Authors: Kiarash Jamali, Dari Kimanius and Sjors Scheres
- Abstract summary: We build ModelAngelo for automated model building of proteins in cryo-EM maps.
Recent advances in machine learning applications to protein structure prediction show potential for automating this process.
ModelAngelo outperforms the state-of-the-art and approximates manual building for cryo-EM maps with resolutions better than 3.5 rA.
- Score: 1.2891210250935146
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Electron cryo-microscopy (cryo-EM) produces three-dimensional (3D) maps of
the electrostatic potential of biological macromolecules, including proteins.
At sufficient resolution, the cryo-EM maps, along with some knowledge about the
imaged molecules, allow de novo atomic modelling. Typically, this is done
through a laborious manual process. Recent advances in machine learning
applications to protein structure prediction show potential for automating this
process. Taking inspiration from these techniques, we have built ModelAngelo
for automated model building of proteins in cryo-EM maps. ModelAngelo first
uses a residual convolutional neural network (CNN) to initialize a graph
representation with nodes assigned to individual amino acids of the proteins in
the map and edges representing the protein chain. The graph is then refined
with a graph neural network (GNN) that combines the cryo-EM data, the amino
acid sequence data and prior knowledge about protein geometries. The GNN
refines the geometry of the protein chain and classifies the amino acids for
each of its nodes. The final graph is post-processed with a hidden Markov model
(HMM) search to map each protein chain to entries in a user provided sequence
file. Application to 28 test cases shows that ModelAngelo outperforms the
state-of-the-art and approximates manual building for cryo-EM maps with
resolutions better than 3.5 \r{A}.
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