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CoreCut Package - Installation and Usage Summary

What Was Created

I've successfully created a complete, pip-installable Python package called CoreCut that extracts structural cores from protein families using Foldseek alignments.

Package Structure

corecut/
├── corecut/                     # Main package
│   ├── __init__.py             # Package initialization
│   ├── cli.py                  # Command-line interface
│   ├── core_extractor.py       # Core extraction logic
│   └── foldseek_utils.py       # Foldseek interaction utilities
├── tests/                      # Test suite
│   ├── __init__.py
│   ├── test_core_extractor.py
│   └── test_foldseek_utils.py
├── examples/                   # Usage examples
│   └── usage_example.py
├── demo/                       # Demonstration script
│   └── demo.py
├── dist/                       # Built packages
│   ├── corecut-0.1.0.tar.gz
│   └── corecut-0.1.0-py3-none-any.whl
├── README.md                   # Comprehensive documentation
├── CHANGELOG.md               # Version history
├── LICENSE                    # MIT license
├── pyproject.toml            # Modern Python packaging config
├── setup.py                  # Fallback setup configuration
└── MANIFEST.in               # Package manifest

Installation

Method 1: From Source (Current)

cd /home/cactuskid/projects/corecut
pip install -e .

Method 2: From Built Package

pip install dist/corecut-0.1.0-py3-none-any.whl

Method 3: When Published (Future)

pip install corecut

Dependencies

External Requirements

Python Dependencies (Auto-installed)

  • pandas >= 1.3.0
  • numpy >= 1.20.0
  • biopython >= 1.79
  • tqdm >= 4.60.0

Usage

Command Line Interface

# Basic usage
corecut /path/to/pdb_files/

# With custom parameters
corecut /path/to/pdb_files/ \
    --output-dir results/ \
    --hit-thresh 0.9 \
    --min-thresh 0.7

# Using existing Foldseek results
corecut /path/to/pdb_files/ \
    --foldseek-results existing_results.m8

Programmatic Usage

from corecut import extract_core, run_foldseek_search

# Run Foldseek comparison
run_foldseek_search(
    input_folder="/path/to/pdb/files",
    output_path="foldseek_results.m8"
)

# Extract cores
extract_core(
    resdf_path="foldseek_results.m8",
    outfile="core_results.csv",
    hitthresh=0.8,
    minthresh=0.6
)

Output

Files Created

  • core_extraction_results.csv - Core boundary data
  • core_structs/ - Core region PDB files
  • nter_structs/ - N-terminal region PDB files
  • cter_structs/ - C-terminal region PDB files
  • foldseek_results.m8 - Raw Foldseek alignments

CSV Format

,min,max,len
protein1,20,79,100
protein2,15,74,90
protein3,20,74,95

Algorithm Overview

  1. Structure Comparison: Uses Foldseek for all-vs-all structural alignments
  2. Alignment Analysis: Maps alignment regions to identify conserved positions
  3. Core Definition: Finds positions aligned in ≥ hit_thresh proportion of structures
  4. Fallback Logic: If no core found, uses min_thresh as cutoff
  5. Structure Extraction: Uses BioPython to extract and save core/terminal regions

Features

✅ Complete pip package with proper structure
✅ Command-line tool with comprehensive options
✅ Python library for programmatic use
✅ Automatic dependency management
✅ Comprehensive documentation
✅ Test suite with pytest
✅ Example scripts and demonstrations
✅ Error handling and progress reporting
✅ Flexible configuration options
✅ Modern packaging (pyproject.toml + setup.py)

Quality Assurance

  • ✅ Package installs correctly
  • ✅ Command-line interface works
  • ✅ All tests pass
  • ✅ Package builds for distribution
  • ✅ Demo script shows functionality
  • ✅ Comprehensive documentation

Next Steps for Distribution

  1. Create GitHub repository
  2. Set up CI/CD (GitHub Actions)
  3. Publish to PyPI: twine upload dist/*
  4. Add more tests for edge cases
  5. Create Docker image with Foldseek included
  6. Add conda package recipe

The CoreCut package is now ready for use and distribution!