DeepFrag: An Open-Source Browser App for Deep-Learning Lead Optimization

Lead optimization,
a critical step in early stage drug discovery,
involves making chemical modifications to a small-molecule ligand
to improve properties such as binding affinity. We recently developed
DeepFrag, a deep-learning model capable of recommending such modifications.
Though a powerful hypothesis-generating tool, DeepFrag is currently
implemented in Python and so requires a certain degree of computational
expertise. To encourage broader adoption, we have created the DeepFrag
browser app, which provides a user-friendly graphical user interface
that runs the DeepFrag model in users’ web browsers. The browser
app does not require users to upload their molecular structures to
a third-party server, nor does it require the separate installation
of any third-party software. We are hopeful that the app will be a
useful tool for both researchers and students. It can be accessed
free of charge, without registration, at http://durrantlab.com/deepfrag. The source code is also available at http://git.durrantlab.com/jdurrant/deepfrag-app, released under the terms of the open-source Apache License, Version
2.0.