TITLE: Image Processing and 3D Reconstruction
AUTHORS: Annan SI Cook

[DESCRIPTION]
This workflow was used to analyze a Krios dataset of the PI3KC3-C1/RAB1A Complex and generate a reconstruction of three distinct conformational states of the VPS34 lipid kinase domain.

[STEPS]
SECTION: Data Import
1. Import the raw Cryo-EM data sets into cryoSPARC v3.
SECTION: Motion Correction and Fourier Cropping
2. Apply motion correction to the super-resolution movies.
SECTION: Motion Correction and Fourier Cropping
3. Perform Fourier cropping 2x on the motion-corrected data using cryoSPARC's implementation of Patch Motion Correction.
SECTION: CTF Determination
4. Use cryoSPARC's Patch CTF Estimation for Contrast Transfer Function (CTF) determination.
SECTION: Particle Picking and Training a Model
5. Manually pick single particles from a selection of micrographs covering a range of defocus values.
SECTION: Particle Picking and Training a Model
6. Train a particle-picking model using Topaz.
SECTION: Particle Extraction and Binning
7. Extract particles with an appropriate box size (e.g., 400x400x400 or ~1.5x the diameter of a single PI3K complex) to ensure retention of delocalized CTF information. 
SECTION: Particle Extraction and Binning
8. Optionally, bin the extracted particles 4x to increase computational speed for subsequent processing.
SECTION: Initial 2D Classification
9. Apply two-dimensional (2D) classification to the extracted particles.
SECTION: Initial 2D Classification
10. Exclude obvious junk particles from further processing based on the 2D classification results.
SECTION: Heterogeneous Refinement
11. Use a junk class from the early rounds of an ab initio run, along with a map generated using an apo PI3K model in UCSF Chimera using molmap at a resolution of 20 Å, for heterogeneous refinement.
SECTION: Heterogeneous Refinement
12. Iterate this process for 3-4 rounds until a healthy substack of particles is evident by 2D classification.
SECTION: Ab Initio Reconstruction and Particle Cleanup
13. Perform a three-class ab initio reconstruction for a final particle cleanup.
SECTION: Ab Initio Reconstruction and Particle Cleanup
14. Should result in a clearly clean class of particles.
SECTION: High-Resolution Refinement
15. Re-extract the particles at a full 400-pixel box size.
SECTION: High-Resolution Refinement
16. Perform homogeneous refinement using the ab-initio model and the clean particle stack to generate a high-resolution model and particle alignments for downstream classification.
SECTION: 3D Classification without Alignment
17. Conduct 3D classification without alignment using a large mask on the putative kinase domain and create 50 classes.
SECTION: Selection of Classes for Further Analysis
18. Select the three most populated classes from the group of 50.
SECTION: Heterogeneous Refinement of Selected Classes
19. Perform heterogeneous refinement on the selected classes.
SECTION: 3D-Variability Analysis
20. Perform 3D-variability analysis in cryoSPARC in cluster mode for each population showing strong density for the kinase domain.
SECTION: 3D-Variability Analysis
21. Using the clusters containing the strongest density, perform non-uniform refinements on each.
SECTION: Local Refinement
22. Conduct local refinement on three parts of the complex: VPS15 pseudokinase domain, RAB1A interface region, and BECN1/ATG14 BARA dimer domain.
SECTION: Local Refinement
23. For VPS34 Kinase containing classes - perform local refinement with a mask aligned to the particular pose of the kinase domain.
SECTION: Local Refinement
24. Create masks for these regions using UCSF ChimeraX Volume Tools.
SECTION: Combining Refined Maps
25. Combine the locally refined maps, which correspond to distinct kinase conformations, using UCSF ChimeraX with the `vop maximum` command.
SECTION: Model Building and Visualization
26. Utilize the combined maps for model building and visualization of the structures.