This challenge aims to motivate the community to benchmark, evaluate, and advance single-particle cryo-EM data processing workflows designed for data with conformational heterogeneity.
We provide a synthetic particle dataset containing conformations extracted from an unbiased atomistic molecular dynamics simulation, along with the sequence of the simulated protein. We challenge participants to determine an ensemble of atomic models that best represents the conformational dynamics of the protein.
We seek to motivate the community to develop new techniques and/or adapt existing workflows to reconstruct ensembles of atomic models from cryo-EM data containing continuous conformational heterogeneity.
Participants should attempt to:
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This dataset contains particles representing a single protein trajectory and corresponding amino acid sequence.
Entries will be evaluated by the accuracy of the atomic models, how similar the local heterogeneity is to the ground truth, and whether the full conformational change is recovered.
Metrics for this assessment are summarized here:
Rankings will be updated periodically. Primary scoring results will be posted on the challenge home page.
https://docs.google.com/spreadsheets/d/e/2PACX-1vSYfO1derbCvRlExWn2ElT1GhXbZ9KN90lTGOy-0gc-yaBojHdeaNr1K8aRPCoJPNqytmoc3w1D5fQJ/pubhtml?widget=true&headers=false
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Entries can be uploaded and submitted via Google Forms here. An example submission can also be viewed here:
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Please provide:
Workflow summary
Between 10 and 100 atomic models (mmCIF format) representing the conformations present in the dataset
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Each model must be deposited as a separate mmCIF file.
All models must be aligned.
Each model must be complete as follows:
All parameters of the submitted models will be considered in evaluation, except for atomic B-factors and occupancies.
Each model will be weighted equally when calculating evaluation metrics.
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