Noisy Nanodisc 2D Class Averages

2D Classification
1

Hello everyone,

I have a nanodisc dataset that is giving me noisy and unrepresentative 2D class averages. I am looking for help to improve the 2D classes. Protein is ~150kDa in an MSP1D1 ND.

I have tried increasing max resolution, increasing minimum separation distance, turning off max poses, increasing batch size, increasing iterations, increasing/decreasing box size. Further suggestions would be very welcome!

Here are some examples of my attempts:

J938_2d_classes_for_iteration_40
J938_2d_classes_for_iteration_402409×485 150 KB

J376_2d_classes_for_iteration_24
J376_2d_classes_for_iteration_242409×482 229 KB

class_examples
class_examples652×137 50 KB

My best run so far has come after curating 18k particles, this has been difficult to reproduce with other sets of particles.

J307_selected_2_classes(1)
J307_selected_2_classes(1)205×104 5.63 KB

Parameters for best run
5 classes
Max res: 3A
Max alignment res: 3A
Number of iterations: 40
Batchsize: 400

Example Micrograph

J247_raw_data_j247imported013674250343485885609_foilhole_141148_data_137075_137077_20230201_093243_fractions_dwmrc
J247_raw_data_j247imported013674250343485885609_foilhole_141148_data_137075_137077_20230201_093243_fractions_dwmrc960×682 198 KB

Perhaps my problem is upstream of 2D classification?

2

Hi,
are you sure your protein is inside the ND?
A 150KDa membrane protein in a MSP1D1 should stick out of the ND and I can’t see any features in the 2D classes.
Did you perform a reverse affinity chromatography step to remove empty nanodiscs first or just a SEC? I find that just a SEC is usually not enough and a poor indicator of a correct reconstitution.
Good luck.