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ANABAG Handler

This repository provides Python scripts to filter and extract specific antibody-antigen complexes and associated features from the ANABAG dataset.

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What Is ANABAG?

ANABAG (ANnotated AntiBody AntiGen) is a curated dataset of antibody–antigen complexes. It includes:

• 3D structural data (with various formats)
• Per-sequence and per-residue features
• Monthly updates

Before using this repository, you must manually download the ANABAG dataset (see below).

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Step 1: Download the ANABAG Dataset

1. Download from the following link:
   https://zenodo.org/records/15794632

Last update: 24/06/2025

2. Extract the .tar archive:

   tar -xvf data.tar

3. Move the extracted folder into this project directory (i.e., where README.md is located). The directory must be named 'data'.

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Step 2: Set Up the Environment

You need Python 3.10+ and a few Python packages.

If using Conda:

conda create -n anabag_env python=3.10 pandas jupyter numpy matplotlib seaborn
conda activate anabag_env

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Step 3: Select Complexes or Features

Use the main script select_complexes.py to select complexes or features based on your criteria.

Example usage:

python src/select_complexes.py path/to/ANABAG path/to/your_config.config

Example with provided template:

python src/select_complexes.py ./ dataset_info/selection_file_complete.config

📁 Output will be saved in the /my_dataset/ directory:

• /my_dataset/structures: contains selected structures
• /my_dataset/files: contains selected feature files

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Create a Configuration File

The configuration file defines how to filter complexes. It is structured in four sections:

Sections:

• Parameters for: Antigen
• Parameters for: Antibody
• Parameters for: Complex
• Parameters for: Selection (controls what is extracted)

Syntax:

Parameters for: Antigen
SequenceIdentity = SG95AG          # SG20AG, SG40AG, SG60AG, SG80AG, SG95AG, SG100AG
UA_Active_site = 0,8               # Range (min, max)

Parameters for: Selection
per_residue_info = True            # Extract per-residue feature files
formatted_structures = True       # Extract formatted structures
initial_structures = False        # Extract original chain label structures
rosetta_structures = False        # Extract Rosetta-relaxed structures
hetatm_structures = False         # Include hetero atoms

References:

• Example config file: dataset_info/example_configuration
• All possible parameters: dataset_info/complete_dictionnary_of_features.txt
• Explanation of parameters: dataset_info/parameters_dictionnary.md

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📊 Visualize the Data (Optional)

You can preview and analyze selected data using the provided Jupyter notebook.

1. Start Jupyter:

   jupyter notebook

2. Open: src/quick_analysis_example.ipynb

3. Set your dataset path inside the notebook:

   path_to_mydataset = 'path/to/anabag-handler/my_dataset/files'

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🗂️ Project Structure

ANABAG-handler/
├── src/
│   ├── select_complexes.py              # Main selection script
│   └── quick_analysis_example.ipynb     # Optional notebook for visualization
├── dataset_info/
│   ├── selection_file_complete.tsv
│   ├── cluster_informations.tsv
│   ├── per_chain_pdbff_informations.tsv
│   ├── method_resolution.tsv
│   ├── sequences_initial_chain.tsv
│   └── sequences_formated_chain.txt
├── images/
│   └── 3ulu_publi.png                   # Example visual / schema
├── README.md
└── (Place extracted ANABAG dataset here)

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