Modelling of Spongilla lacustris proteome with functional annotations
Main links:
- Link Project in MA (incl. background on project itself)
- Jira-story
Setup:
- Using ColabFold for monomer predictions with AlphaFold without links to sequence databases
- Input from them:
- one tarball for the PDB files
- one tarball for the JSON files
- a CSV file with title and description for each protein
- FASTA file with all sequences (used for sanity checks)
Special features here:
- Description is long multiline text which includes output from functional annotation
- First set of models converted by us to ModelCIF
- Includes generic code for handling of ColabFold setup based on config.json
- Includes test code for conversion of ModelCIF to content displayed in ModelArchive
Content:
- translate2modelcif.py : script to do conversion; compatible with Docker setup from ma-wilkins-import (and script based on code there)
- tests folder with
- custom Docker setup used locally (Mac; with extra libraries for testing) and on work machine (managed CentOS with old docker version)
- test_modelCIF_MA.py to convert ModelCIF to content displayed in ModelArchive (needs gemmi library)
- test.ipynb and .html for tests performed during development