sokrypton / sokrypton/ColabFold
AF2 with MMseqs2 ColabFold crash: unable to find SCOPdata
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Description
This is fairly new, having run ColabFold 1.5.3 (the workhorse AF2 w/ MMseqs version) quite well last night, but the first job this morning crashed at the "Run Prediction" stage with the following error message––that centers on the inability to load SCOPdata, an interesting dependency that I wasn't aware of! Just in case, I restarted and ran clean ColabFolds twice, and the error recurred exactly as the first time. Thx in advance for your kind help!
ImportError Traceback (most recent call last)
in <cell line: 12>()
10 from colabfold.download import download_alphafold_params, default_data_dir
11 from colabfold.utils import setup_logging
---> 12 from colabfold.batch import get_queries, run, set_model_type
13 from colabfold.plot import plot_msa_v2
14
5 frames
/content/alphafold/data/mmcif_parsing.py in
22 from absl import logging
23 from Bio import PDB
---> 24 from Bio.Data import SCOPData
25
26 # Type aliases:
ImportError: cannot import name 'SCOPData' from 'Bio.Data' (/usr/local/lib/python3.10/dist-packages/Bio/Data/init.py)
Contributor guide
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 with the ColabFold 1.5.3 notebook at the Run Prediction stage and inspect the traceback from colabfold.batch into alphafold/data/mmcif_parsing.py. Check the Python 3.10 environment and the Bio.Data import involved in the SCOPData failure. Done means the notebook reaches prediction without this ImportError.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- bioinformatics, machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100