Pseudo-symmetric complex reconstruction


I am trying to solve a complex structure of a protein complex. Protein A is an octamer and the total MW is around 800 kDa. Protein B is a hexamer ATPase (~180 kDa in total) and binds to protein A when activated by ATP.

I collected a couple of datasets using different strategies to reconstruct the complex but got confused about where I did wrong…The target is to get like different intermediate states during ATPase turnover, but till now, only one dataset gave me resonable reconstruction.

In one of the datasets, I got like 30k particles in final reconstruction out of 1 million particles (6k micrographs). Some of the typical 2D classes after final refinement↓

In another dataset, 2D classification in a mask diameter of the whole complex seems to be unable to distinguish A+B from just adjacent A+A (unfortunately, particles seem to be clustered even I tried lower protein conc. ). So I just excluded trash classes in the mask diameter of A and move onto hetero-refine (like what I did in the first dataset). But, in hetero-refine in C1, the refinement seems to be centered on A and only smeared density around it was observed. I am not sure, but is this something driven by the symmetry of A and low population of complex particles?

I found several similar topics here, and tried like symmetry expansion→3D classification w/o alignment in cryoSPARC, but it didn’t work… I’m considering to try with Relion symmetry relaxation though.

Do you have any advice on case like this?
Many thanks!

smeared density in the second dataset