IDL-PPBopt

Code for "IDL-PPBopt: A Strategy for Prediction and Optimization of Human Plasma Protein Binding of Compounds via an Interpretable Deep Learning Method"

Requirements

That version of the model uses cuda.

• python 3.7
• pytorch 1.5.0
• openbabel 2.4.1
• rdkit
• scikit learn
• scipy
• cairosvg

Installation

Using conda:

# 1- Clone that repo.
git clone https://github.com/Aml-Hassan-Abd-El-hamid/IDL-PPBopt.git

# 2- Create conda environment form inside the repo folder.
cd IDL-PPBopt
conda env create -f environment.yml

# 3- Activate conda environment.
conda activate IDL_PPBopt_cuda

# 4- Build and install the modules insider the repo folder.
make build
make install

Usage

The above instructions allow the import of two new modules: AttentiveFP and IDLPPBopt. Have a look at the examples for detailed use instructions.

Model

The iPPB model was trained with AttentiveFP algorithm and saved in the "saved_models" file.

PPB prediction and second-level chemical rules' derivation for PPB optimization

1. Write the given molecules to input_compounds.csv file.
2. Run IDL-PPBopt.ipynb in jupyter notebook.