AAA+ Unfoldase
Dataset
This AAA+ Unfoldase dataset was kindly provided to us by John Rubinstein . The original paper on this dataset was published in Elife 2017, entitled Structure of a AAA+ unfoldase in the process of unfolding substrate .
Learning objectives
2D classification & multi-class ab-initio reconstruction.
Title | Value |
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Title | |
Description | Leave empty |
Directory | |
Create Workspace | Enable |
Parameter | Value |
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Particle meta path |
This should take less than 10 seconds.
Parameter | Value |
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Circular mask diameter (A) | |
Number of GPUs to parallelize |
Choose a set of 2D classes that look sharp and display secondary structure features. Make sure not to exclude classes showing the active state of the unfoldase, as we will use these downstream in ab-initio! However, you should exclude classes that converged to two copies of the "side view", as these particles are from crowded regions of the micrograph.
You should end up with around 133K particles.
Parameter | Value |
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Number of Ab-Initio classes |
Inputs | Source |
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Particle stacks | Particles from the more populated, inactive, 6-fold symmetric state |
Initial volume | Use the corresponding volume class |
Parameter | Value |
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Symmetry |
Launch this job in parallel with the previous homogeneous refinement (using particles from ab-initio reconstruction).
Inputs | Source |
---|---|
Particle stacks | Particles from the less populated, active, asymmetric state |
Initial volume | Use the corresponding volume class |
Use default parameters