COFOLDER
COFOLDER is a collection of command-line workflows for protein-ligand co-folding and pre-cofolding diagnostics.
The supported public entry points are:
bias: inspect protein and ligand reference overlap directly fromsystem.yamlvalidate: run a single runner-backed co-folding workflowscreen: run validate-style workflows across a ligand libraryoracle: return one scalar metric from a runner-backed run
COFOLDER has a backend-free base install for configuration, input handling, resource
access, and analysis-independent library paths. Install the analysis extra for
clustering, affinity statistics, interaction processing, and plotting; prediction
workflows additionally use one backend extra. Structural-confidence outputs,
validation metrics, and affinity-related outputs are treated as distinct concepts;
structural confidence should not be described as a proxy for binding affinity.
Start Here
If you are new to the repository, use this path:
- Install COFOLDER with the backend you need. See docs/getting-started/installation.md.
- Run your first command. See docs/getting-started/quickstart.md.
- Pick the workflow that matches your task. See docs/user-guide/overview.md.
- Move to worked examples and hands-on tutorials. Use examples/README.md, docs/tutorials/index.md, and tutorials/README.md.
Installation
COFOLDER requires Python 3.11 or 3.12.
Base install:
git clone https://github.com/CDDLeiden/COFOLDER.git
cd COFOLDER
python -m pip install -e .
Recommended analysis and prediction install with the default backend:
python -m pip install -e ".[analysis,boltz2]"
OpenFold3 install:
python -m pip install -e ".[analysis,openfold3]"
cofolder-tools setup-openfold3
The bias workflow does not require a co-folding backend. Install .[analysis] for
its complete plotting artifact set and other optional analysis features.
Installed setup and data-preparation helpers are grouped under cofolder-tools.
Run cofolder-tools --help to copy the bundled examples, prepare OpenFold3,
install MMseqs2, or fetch/build bias-training data.
Common Commands
cofolder [-h] [-v] {bias,validate,screen,oracle}
Examples:
cofolder bias \
--system_path system.yaml \
--wrk_dir ./bias_out \
--custom_protein_reference_path custom_protein.csv \
--custom_ligand_reference_path custom_ligand.csv
cofolder validate \
-s examples/system.yaml \
-o examples/options.yaml \
-w ./validate_out
cofolder screen \
-s examples/system_screen.yaml \
-o examples/options.yaml \
-c examples/ligand_screen.csv \
--col_id compound_id \
--ligand_chain B --smiles_column smiles \
-w ./screen_out
cofolder oracle \
-s examples/system.yaml \
-o examples/options.yaml \
--input_smiles "CCO" \
--output_metric system__confidence_score \
--scoring_functions confidence_metrics \
--aggregate first
For detailed setup, workflow selection, and command options, use:
For CLI-independent execution and backend integration, use the Python API flow references:
Repository Guide
These top-level paths now have distinct roles:
docs/: authoritative public documentation for installation, workflow selection, tutorials, and API referenceexamples/: copyable input files and small fixtures used by quickstarts and docstutorials/: interactive notebook tutorials for hands-on explorationscripts/: helper utilities for optional setup and bias-data preparationLICENSEandTHIRD_PARTY_SOFTWARE.md: repository licensing and third-party attribution
For a short tour of how these pieces fit together, see docs/getting-started/repository-tour.md.
Folder-Specific Notes
- examples/README.md explains which example files to use first.
- tutorials/README.md gives a recommended notebook order.
- scripts/README.md separates supported helpers from maintainer-oriented utilities.
Documentation
The MkDocs site is the best public-facing documentation surface. To build it locally:
python -m pip install -e ".[docs]"
mkdocs serve
The docs site complements, rather than replaces, the repository tutorials:
docs/is the curated reading pathexamples/is the copy-and-run pathtutorials/is the interactive notebook path
Licenses
COFOLDER is released under the MIT License. Third-party attributions for adapted or bundled components are listed in THIRD_PARTY_SOFTWARE.md.
Citation metadata for COFOLDER 1.0.0 is provided in CITATION.cff. The publication and archival identifier will be added after those records are final.
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Total release size: 1.2 MB
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