Cryptic Pockets Database

A pipeline for analyzing protein structures to identify cryptic pockets.

Installation

Create and activate the conda environment:

conda env create -f environment.yml
conda activate database

Before running the pipeline, set the FETCH_PATH in monomer_calcs.py to your local directory for CIF files.

Usage

Run the pipeline:

python monomer_calcs.py [options]

Options:

• --n_jobs: Number of parallel jobs (default: 16)
• --input_list: Use predefined PDB IDs
• --update_previous: Update existing data
• --max_res: Maximum resolution threshold in Å (default: 2.5)
• --custom_folder: Custom data folder (default: data)

Project Structure

• monomer_calcs.py: Main pipeline for data collection and processing
• scoring_function.py: Scoring system for pocket analysis
• get_sites.py: Identifies and clusters binding sites
• refine_smiles.py: Processes and refines ligand information

Data Organization

• data/: Main data directory
  • monomer_calcs/: Processed structure data
  • xyz_files/: Structure coordinates
  • xyz_files_local/: Local structure coordinates
  • checkpoints/: Processing checkpoints