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

J Chem Inf Model. 2021 Jun 28;61(6):2523-2529. doi: 10.1021/acs.jcim.1c00103. Epub 2021 May 24.


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 The source code is also available at, released under the terms of the open-source Apache License, Version 2.0.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Computers
  • Deep Learning*
  • Humans
  • Internet
  • Ligands
  • Mobile Applications*
  • Software
  • Web Browser


  • Ligands