psearch 0.0.1

PSearch: ligand-based pharmacophore modeling and screening

PSearch - 3D ligand-based pharmacophore modeling

PSearch is a tool to automatically generate 3D ligand-based pharmacophore models.

Installation

pip install psearch

Dependency

pmapper >= 0.2

Example

Creation of ligand-based pharmacophore models

It is recommended to create an empty dir which would be your $PROJECT_DIR and copy an input file to that location.
There are two steps of pharmacophore model generation.

1. Data set preparation. It takes as input a comma-separated SMILES file containing SMILES, compound id, activity value. It splits the input on active and inactive subsets, generates stereoisomers and conformers, creates databases of active and inactive compounds with labeled pharmacophore features.

python3 prepare_datatset.py -i $PROJECT_DIR/input.smi -l 6 -u 8 -c 4

-i - path to the input file;
-u - threshold to define active compounds (compounds with activity value >= threshold are considered active);
-l - threshold to define inactive compounds (compounds with activity value <= threshold are considered inactive);
-c - number of CPUs to use.
There are other arguments available to tweak data set preparation. To get the full list of arguments run python3 prepare_datatset.py -h

2. Model building.

python3 psearch.py -p $PROJECT_DIR -t 0.4 -c 4

-p - path to the project dir;
-t - threshold for compound clustering to create training sets;
-c- number of CPUs to use

Virtual screening with pharmacophore models

TODO

Documentation

All scripts have `-h' argument to retrieve descriptions of all available options and arguments.

Authors

Alina Kutlushina, Pavel Polishchuk

Citation

Ligand-Based Pharmacophore Modeling Using Novel 3D Pharmacophore Signatures
Alina Kutlushina, Aigul Khakimova, Timur Madzhidov, Pavel Polishchuk
Molecules 2018, 23(12), 3094
https://doi.org/10.3390/molecules23123094

License

BSD-3 clause