I have a pretty good 3D structure of a protein we are working on with a lot of heterogeneity in a certain section. I have used multiple refinements, masking, and refinements with finer angular sampling to get a structure that has most of the features we are looking for, but it represents a very small percentage of the particles originally picked, and is at >10 A resolution. I'd like to increase that number of particles/resolution by using this 3D consensus to make 2D references and then run that through autopicking. Hopefully that will net me more high quality particles that contain the subunits of interest.
Is there a way to do this Relion? Chimera?
Also, is this introducing bias in any way? The 2D classes would be generated from a 3D structure that was generated from the same raw data, so I wouldn't think so, but any advice on that would be great.
Thanks!
Austin Dixon
Rockefeller University
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