GATA3-extension Mutants Rewire Lineage Identity in Luminal Breast cancer

This repository contains the scripts for the analysis of the effect of GATA protein mutants on its ability to bind DNA.

Setup

Create a conda environment

conda env create -f environment.yml -n gata
conda activate gata

Setup AF-pipeline

git clone --recursive https://github.com/isblab/af_pipeline.git

Add $PATH_TO_AF_PIPELINE to ~/.bash_profile. Then run,

source ~/.bash_profile

Analysis

Step 1: To generate the AF3 input JSON files, run the following command

python gata_analysis.py -i

Step 2: Use the input JSON file to obtain predictions from the AF3 webserver.

Step 3: For the performing the analysis, run the following command,

python gata_analysis.py -a

Results

The ./gata_output/ directory contains the following:

• af3_inputs

  • dimer.json: AF3 input JSON file. Upload this file on the AF3 webserver to obtain the predictions.

• af3_preds: contains the best predicted structure (based on the ranking score) obtained from AF3.

• analysis

  • rb_dir_path.json: JSON file containing the paths to the rigid_body .pdb file obtained from AF-Pipeline.
  • rb_figures: ChimeraX figures for the riggid bodies obtained from AF-Pipeline.
  • rigid_body: contains the rigid bodies extracted from the AF3 predictions using AF-Pipeline.

Information

Author(s): Kartik Majila

Date: Aug 19, 2026

License: CC BY-SA 4.0 This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License.

Testable: Yes

Publication Nivedhya Venas, Mrunal Ratnaparkhi, Kartik Majila, Shruthi Viswanath, Dimple Notani, Radhakrishnan Sabarinathan, GATA3-extension Mutants Rewire Lineage Identity in Luminal Breast cancer, submitted.