STOPLIGHT Score Calculator: Used to predict/calculate varies properties and assign a hit progression score to a given chemical or list of chemicals. If you use please cite [INSERT CITATION HERE]. There is a webserver that runs these models, but for large numbers of compounds, running locally using this code is much more effective
Install the requirements from the requirements.txt file. Additionally, if you want to run the webserver, you need to install flask and gunicorn
After downloading, Stoplight/stoplight.py can be called from the command line with python stoplight.py --help
--infile is required and is the file location for a csv of SMILES to predict properties for. Requires that csv has header and is comma seperated
--smiles_col is the name of the column containing the SMILES strings of interest. Defaults to "SMILES"
--outfile is the file location of where the output csv file should go. Defaults to \[current-working-directory\]/stoplight_results.csv
--props is all the properties you want to calculate. See stoplight_properties_help.txt for details
--drop_invalid by default, invalid smiles will be saved in the output, but listed as invalid and given NA values. Using this drops these (silently) from the output file
This repository also contains the code to run a local webserver (or host your own). You can start the server by running qunicorn wsqi:app (or using the development flask server by setting the FLASK_APP variable: $env:FLASK_APP = "app" on windows or export FLASK_ENV=app on unix). From that access 127.0.0.1:5000 to view the local server
Thanks to JSME for a free and easy to use molecule editor for webpages Bienfait, B., Ertl, P. JSME: a free molecule editor in JavaScript. J Cheminform 5, 24 (2013). https://doi.org/10.1186/1758-2946-5-24