CombFold Pipeline

This CombFold Pipeline, predicts the structure of large protein complexes starting from the sequences of chains in the complex (up to at least 18,000 amino acids and 32 subunits).

Pipeline Structure

This Pipeline uses the following three Capsules:

• CombFold - prepare fasta

• Streamlit ColabFold: AlphaFold2 using MMseqs2

• CombFold - Combinatorial Assembly

The final Pipeline should look like the following.

Final CombFold Pipeline

Create Data Assets

Create a "json" subfolder inside the /data folder and upload a subunit json (json is described in the CombFold capsules README and on GitHub).

Either create a Data Asset containing the ColabFold Model from the public Code Ocean Bucket or download from the Alphafold Github repository (https://github.com/google-deepmind/alphafold). If you want to use the public bucket fill in the following information as a new data asset:

Alphafold Model

Bucket Name: codeocean-public-data

Path: models/colabfold

Attach Data Assets

Click Manage Data Assets

Attach the ColabFold Model.

Drag the ColabFold Model Data Asset and the "json" folder onto the Pipeline UI.

Create Pipeline

1. Create a new Pipeline and select the indicated Apps from the “Code Ocean Apps” window:

Select Apps From the Pipeline view

• CombFold - prepare fasta

• Streamlit ColabFold: AlphaFold2 using MMseqs2

• CombFold - Combinatorial Assembly

2. Connect “CombFold - prepare fasta” to “Streamlit ColabFold: AlphaFold2 using MMseqs2” using Flatten. Set the Source to “capsule/results/fasta_pairs/*”

   • Flatten passes each output fasta subunit to be processed in parallel by ColabFold.

Set Source and Connection type

2. Connect “Streamlit ColabFold: AlphaFold2 using MMseqs2” to “CombFold - Combinatorial Assembly” using Collect. Set the Source to “capsule/results/*/pdb_files/*”

   • Collect passes all subunits are passed together downstream for assembly.

2. Connect "json" using Default to both Combold Capsules.

3. Connect the "ColabFold model" to the "Streamlit ColabFold: AlphaFold2 using MMseqs2" Capsule using Collect. Set “capsule/data/colabfold” as the Destination.

4. [optional] Connect the “CombFold - prepare fasta” Capsule to the results bucket and provide “pipeline/results/pairs” as the Destination.

5. [optional] Connect the “Streamlit ColabFold: AlphaFold2 using MMseqs2” to the results bucket and provide “pipeline/results/ColabFold” as the Destination.

6. Connect the "CombFold - Combinatorial Assembly Capsule" to the results bucket and provide “pipeline/results/CombFold" as the Destination.

7. To run the Pipeline, click “Reproducible Run” in the top right corner of the webpage.

Viewing Outputs

The output structure can be viewed in the CombFold/make_figure.html file or it can be viewed using the Mol* Viewer in the Apps Library.

CombFold Structure