RosettaCommons / RosettaCommons/RFdiffusion
Cyclic peptide design issues
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- Python
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Description
Hello, I'm a beginner and would like to use RFpeptides to design cyclic peptides that bind to my target protein. I've generated over 2,000 structures for my target protein, but none of them have resulted in a cyclic peptide. I'm worried it might be a script issue. I used the official sample input PDB and the script twice to generate a total of 20 structures, but still haven't found a cyclic peptide. Could you please help me check the following to see if this is a script issue?
#!/bin/bash
prefix=/data/*/job1/output/new_cyclic_binder
num_designs=10
pdb='/data/*job1/7zkr_GABARAP.pdb'
HOTSPOTS='["A51","A52","A50","A48","A62","A65"]'
script="/data/RFdiffusion/scripts/run_inference.py"
$script --config-name base
inference.output_prefix=$prefix
inference.num_designs=$num_designs
'contigmap.contigs=[12-18 A3-117/0]'
inference.input_pdb=$pdb
+inference.cyclic=True
diffuser.T=50
+inference.cyc_chains='a'
+ppi.hotspot_res=$HOTSPOTS
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the reported run command, especially /data/RFdiffusion/scripts/run_inference.py, the 7zkr_GABARAP.pdb input, and the cyclic and chain-related options. Reproduce the command with the sample input and inspect the generated outputs and logs to determine whether cyclic structures are being requested and produced. Done means identifying whether this is a script/configuration problem and documenting the evidence.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100