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psearch.py

README.md

PSearch - 3D ligand-based pharmacophore modeling

PSearch is a Python application to automatically generate 3D pharmacophore models based on a supplied data set of compounds with measured activity values.

Installation

git clone https://github.com/meddwl/psearch
git submodule init
git submodule update

Dependency

rdkit >= 2017.09
networkx >= 1.11

Example

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.

'I.'

  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 - treshold to define active compounds (compounds with activity value >= threshold are considered active);
-l - treshold 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 agruments run python3 prepare_datatset.py -h

  1. 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

'II.'

Authors

Alina Kutlushina, Pavel Polishchuk

Citation

...

License

BSD-3

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