Open-Source software for Fully-automated Protein-based Pharmacophore Modeling and High-throughput Virtual Screening.
OpenPharmaco is currently powered by PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling, developed by Seonghwan Seo, KAIST.
If you are deep learning researcher, please visit PharmacoNet [github]. It provides more functions.
If you have any problems or need help, please add an github issue.
You can get more information at Wiki.
* Tested on Microsoft Window and Mac OS X (Apple Silicon).
# Download Source Codes
git clone https://github.com/SeonghwanSeo/OpenPharmaco.git
# Create Environment
cd OpenPharmaco/
conda env create -f environment.yml
conda activate openph
pip install .
# Start
conda activate openph
openph # or openpharmaco
Paper on arxiv
@article{seo2023pharmaconet,
title = {PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling},
author = {Seo, Seonghwan and Kim, Woo Youn},
journal = {arXiv preprint arXiv:2310.00681},
year = {2023},
url = {https://arxiv.org/abs/2310.00681},
}
- Version 2.0.0
- Performance Improvement (Provisional: PharmacoNet v2)
- SMILES Input (Conformer-free inference)
- Verison 2.1.0:
- Binding Site Detection for Apo Protein Structures
- Pharmacophore Customizing
- Version 3
- Binding Pose Prediction