This is repository for "Transfer Learning-Enabled Ligand Prediction for Ni-Catalyzed Atropselective Suzuki-Miyaura Cross-Coupling Based on Mechanistic Similarity: Leveraging Pd Catalysis Knowledge for Ni Discovery". Paper is available at https://pubs.acs.org/doi/10.1021/jacs.5c00838.

In order to run Jupyter Notebook involved in this repository, several third-party python packages are required. The versions of these packages in our station are listed below. To reproduce the machine learning results, please install packages with same version as below.

rdkit==2024.03.5
numpy==1.24.4
pandas==2.2.2
scikit-learn==1.3.0
scipy==1.11.1
matplotlib==3.7.1
morfeus==0.7.2
xgboost==1.7.6
lightgbm==4.2.0

In addition to installing the aforementioned third-party libraries, you also need to execute the following code in current folder to install the Python package asymopt included with this project.

pip install .

All test were executed under Ubuntu 18.04.

Here we provide several notebooks in code folder to demonstrate how to generate virtual ligand library and perform ligand screening.