Mordred: a novel descriptor calculating software

Moriwaki Hirotomo, Kawashita Norihito, Tian Yu-Shi, Takagi Tatsuya

doi:10.11545/ciqs.2016.0_y4

Descriptors, calculated properties of compounds, are generally used as features for prediction models (such as Multiple Regression Analysis models) in Quantitative Structure-Activity Relationship (QSAR) studies. Plenty of software packages regardless of commercial or non-commercial were developed to calculate such descriptors. PaDEL-descriptor, a well-known free software, which is referenced more than 300 times, can calculate numerous kinds of descriptors and is widely used. However, we found that there are several problems within it. To overcome its disadvantage and provide correct calculations, we developed a novel software package named mordred, which is implemented in Python language. It can be used as a module of Python2 or 3. Python is increasingly used in machine learning, especially in neural networks nowadays. Therefore, the Python coded mordred is easy to be used in constructing machine learning models. At current time, more than 2,000 descriptors including 2D and 3D-descriptors can be calculated in Command line interface (CLI), Web Application, and Python module. Moreover, mordred with its documentation can be obtained from github (https://github.com/mordred-descriptor), are released under the BSD3 license, and can be freely used including commercial purposes and modifications.

Mordred: a novel descriptor calculating software

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