3D Variability Mask

Hi,

I am attempting to model the continuous motion of a 60 kda portion of an 330 kda protein and I have already isolated the different “states” of this protein’s motion through 3D classifications. My question is, since I know the direction of motion, should I do 3D variability with a mask that will capture the space in which this segment will move, or should I use the mask that comes from the output of the refinement and the program will figure out the motion? Any advice as far as masking in this situation would be helpful for my understanding.

Thanks in advance!

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Hi @adtaheri,

This is a great question! If your primary goal is to look at the continuous motion through all of the different states that you have obtained through 3D classification, likely the best way of resolving this motion would be to ensure that the mask you provide covers all of the states that you expect the complex to move through. If the mask doesn’t cover regions in which the protein may actually move through, the 3D variability won’t be able to detect flexibility in that area. In doing this, you should also input all particles from all 3D classifications into the 3D Variability job, so that all states contribute to solving the variability modes.

If you are also interested in observing heterogeneity in the rest of the protein, you should provide a mask that covers the entire complex in addition to the whole 60 kda flexible sub-region too. Please let me know if this helps! You can also find more information in our 3D Variability tutorial, as well as our 3D Variability Webinar from this past June.

Best,
Michael

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Hi Michael - in some of the cases covered in the tutorial (the spliceosome and NaV channel particularly) the changes are pretty dramatic, implying the use of a very generous mask.

However for membrane proteins the general advice as I understand it is to mask them pretty tightly around the TM to exclude nanodisc/detergent heterogeneity.

In general if we don’t know the location/amplitude of heterogeneity, would you then try 3D-VA with several different masks, perhaps by dilating the mask to differing extents? I guess what I mean is, how do we know if we are missing heterogeneity because we are masking too tightly?

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@mmclean thank you for the response. A quick follow up: would you recommend using the mask intended for use for 3D variability (a wide mask covering all states) during the refinement step required prior to the 3D variability job? Or just stick to a mask appropriate for the structure being refined with all the particles from all the different states.

Hi all,

@olibclarke Hmm, this is a good question for sure. Naively, I would suggest that experimenting with different mask tightness would probably be the best approach, and this can be informed by how much flexibility you suspect (e.g. if you are only looking for small scale motion, then tighter masks like the ones outputted from refinement may be okay). I haven’t experimented enough with mask tightness to give much insight on this unfortunately – possibly @apunjani could give more information than I can.

@adtaheri Running a consensus refinement with all particles & a mask that includes the whole 330 kda complex (plus the entirety of the flexible region) may be the best option – this way, you end up with all particles aligned to the same common reference, which is important as otherwise it’s possible that 3D variability could end up detecting small differences in rotation between each class, rather than the desired movement. This consensus refinement might not reach quite as high resolution as any of the individual 3D classifications, but for the purposes of 3D Variability, this is the approach we recommended in our tutorial.

Best,
Michael

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