QEPPI 0.1.7

Calculation module of QEPPI

QEPPI

Quantitative Estimate Index for Compounds Targeting Protein-Protein Interactions

Calculation QEPPI with using Google Colab

We have made it so that you can use Google Colab to calculate QEPPI from SMILES without creating your own environment.
If you have a lot of SMILES to calculate, please convert the SMILES to SDF files.

Mininal Environment Setup (Only QEPPI calculation)

We setup it on a Mac (macOS10.15.7), but I'm sure it will run fine on other platforms such as Linux.

miniconda3-4.3.30
Python 3.7.9
rdkit=2020.09.1.0
numpy=1.20.1
pandas=1.2.3

We also confirmed that QEPPI works with the installation of RDKit by pip install rdkit-pypi instead of the conda environment. (see notebook)

Test

Test it when you are done with the setup. If the test passes, the QEPPI calculation has been successfully performed. (We used pytest version is 6.2.2)

pytest -v

QEPPI Calculaton example

# for .sdf
python calc_QEPPI.py --sdf PATH_TO_YOUR_COMPOUND.sdf --out PATH_TO_OUTPUT.csv

# for .csv ("A column name of "SMILES" is required.")
python calc_QEPPI.py --csv PATH_TO_YOUR_COMPOUND.csv --out PATH_TO_OUTPUT.csv

If you want to implement your own, the following is a sample code.

import qeppi as ppi
from rdkit.Chem import SDMolSupplier

q = ppi.QEPPI_Calculator()
q.load("./model/QEPPI.model")

ppi_s = SDMolSupplier("PATH_TO_SDF/YOUR_COMPOUND.sdf")
ppi_mols = [mol for mol in ppi_s if mol is not None]
result = list(map(q.qeppi, ppi_mols))

Reference

• Kosugi T, Ohue M. Quantitative estimate of protein-protein interaction targeting drug-likeness. In Proceedings of The 18th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2021). (accepted) ChemRxiv, Preprint. 2021. doi:10.33774/chemrxiv-2021-psqq4-v2
• Kosugi T, Ohue M. Development of a quantitative estimate index for early-stage screening of compounds targeting protein-protein interactions. (under revision)