parslfold

Fold proteins in parallel using Parsl.

Supported folding methods: - Chai-1 - ESMFold

Installation

On Workstations (rbdgx, lambda, etc.)

To install the package, run the following command: bash conda create -n parslfold-env python==3.10 conda activate parslfold-env git clone git@github.com:ramanathanlab/parslfold.git cd parslfold pip install -U pip setuptools wheel pip install -e .

On Polaris

To install the package on Polaris@ALCF, run the following commands before the pip install command: bash module use /soft/modulefiles; module load conda conda create -n parslfold-env python==3.10 conda activate parslfold-env git clone git@github.com:ramanathanlab/parslfold.git cd parslfold pip install -U pip setuptools wheel pip install -e .

On Aurora

Make sure to be on a login node (not compute).

```bash git clone git@github.com:ramanathanlab/parslfold.git cd parslfold module load frameworks pip install -U pip setuptools wheel pip install -e .

Command above will install packages in your .local directory.

Add it to the path like so (add this in your .bashrc)

export PATH=/home//.local/aurora/frameworks/2024.2.1_u1/bin:$PATH ```

Usage

To fold a set of proteins, run the following command (see example YAML config for details): bash nohup python -m parslfold.main --config examples/workstation_config.yaml &> nohup.log &

The output folder structure will look like this: examples/output/ ├── config.yaml ├── parsl │   └── 000 │   ├── htex │   │   ├── block-0 │   │   │   └── 082881fe477f │   │   │   ├── manager.log │   │   │   ├── worker_0.log │   │   │   └── worker_1.log │   │   └── interchange.log │   ├── parsl.log │   └── submit_scripts │   ├── parsl.htex.block-0.1737608324.8257468.sh │   ├── parsl.htex.block-0.1737608324.8257468.sh.ec │   ├── parsl.htex.block-0.1737608324.8257468.sh.err │   └── parsl.htex.block-0.1737608324.8257468.sh.out └── structures ├── uniprotkb_accession_A0LFF8_OR_accession_2024_12_19_seq_0 │   ├── input.fasta │   ├── pred.model_idx_0.pdb │   └── scores.model_idx_0.npz └── uniprotkb_accession_A0LFF8_OR_accession_2024_12_19_seq_1 ├── input.fasta ├── pred.model_idx_4.pdb └── scores.model_idx_4.npz

• config.yaml: The configuration file used to run the folding.
• parsl/: The Parsl logs and submit scripts (containing stdout and stderr).
• structures/: The folded protein structures.
  • input.fasta: The input sequence used for folding.
  • pred.model_idx_X.pdb: The highest confidence folded protein structure.
  • scores.model_idx_X.npz: The scores for the folded protein structure.

Notes

• We only keep the highest confidence folded protein structure and its scores.
• The subdirectories within structures/ are named based on the input sequence fasta file name and the index of the sequence in the file (e.g., <fasta-name>_seq_X).
• See examples/chai1_example.py for a quick example of how to fold a protein using the Chai-1 method in our package. This is the same core functionality as the main script, but without the parallelism provided by Parsl.

Contributing

For development, it is recommended to use a virtual environment. The following commands will create a virtual environment, install the package in editable mode, and install the pre-commit hooks. bash python -m venv parslfold-env source parslfold-venv/bin/activate pip install -U pip setuptools wheel pip install -e '.[dev,docs]' pre-commit install To test the code, run the following command: bash pre-commit run --all-files tox -e py310