DOPtools: a Python platform for descriptor calculation and model optimization

Abstract

The DOPtools (Descriptors and Optimization tools) platform is a Python library for the calculation of chemical descriptors, hyperparameter optimization, and building and validation of QSPR models. In addition to the Python code that can be integrated in custom scripts, it provides a command line interface for the automatic calculation of various descriptors and for eventual hyperparameter optimization of statistical models, enabling its use in server applications for QSPR modeling. It is especially suited for modeling reaction properties via functions that calculate descriptors for all reaction components. While a variety of existing tools and libraries can calculate various molecular descriptors, their output format is often unique, which complicates their integration with standard machine learning libraries. DOPtools provides a unified API for the calculated descriptors as input for the scikit-learn library. The modular nature of the code allows easy addition of algorithms if required by the end user. The code for the platform is freely available at GitHub and can be installed through PyPI.