A simple pharmacophore modeling toolkit
Project description
A Simple Pharmacophore-Toolkit
The Pharmacophore-Toolkit is built on RDKit and allows for building simple pharmacophore models. The Pharmacophore-Toolset can generate models from crystal structures, docking poses, or SMILES string. To generate a 3D model, a .pml file will be generated. This files contains scripts to generate spheres with color and XYZ coordinates defined. The final 3D image can be rendered in PyMOL.
Documentation for the project can be found here.
Install
You can install the Pharmacophore-Toolkit using pip:
pip install pharmacophore-toolkit
Alternatively, the environment can be created by cloning the repository and then running the following conda script:
conda env create -f environment.yaml
[!NOTE] Note: The Pharmacophore-Toolkit relies on cairosvg to create images before being converted into .png format. Depending on your workstation/machine, the CairoSVG package will need to be installed manually. Installation instructions can be found here. If it is not already installed on your machine globally, users can try conda to install cairosvg:
conda install conda-forge::cairosvg
Conda installation solved the problem on my machine, but may differ with yours.
Tutorials
Tutorials are written as JupyterNotebooks and can be found here. The Pharmacophore-Toolkit can generate several types of images:
Example Images
3D Model
A 3D conformation of molecules and alignment was performed using RDKit. Spheres can be generated for each query molecule to highlight pharmacophore features, such as Hydrogen Bond Donor/Acceptor, Hydrophobic, Aromatic, etc. The molecules can be generated in 3D using two methods:
2D Model
The pharmacophore features can also be depicted as a 2D image, where each atom is highlighted with their respective pharmacophore features.
Similarity Map
For funsies, a method to generate Similarity Maps are also available. Final image generation requires Cairo installation. Additional information on how Similarity Maps work can be found on the RDKit blog.
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