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Deep2Lead: A distributed deep learning application for small molecule lead optimization

Quantitative Methods 2021-08-12 v1 Machine Learning

Abstract

Lead optimization is a key step in drug discovery to produce potent and selective compounds. Historically, in silico screening and structure-based small molecule designing facilitated the processes. Although the recent application of deep learning to drug discovery piloted the possibility of their in silico application lead optimization steps, the real-world application is lacking due to the tool availability. Here, we developed a single user interface application, called Deep2Lead. Our web-based application integrates VAE and DeepPurpose DTI and allows a user to quickly perform a lead optimization task with no prior programming experience.

Keywords

Cite

@article{arxiv.2108.05183,
  title  = {Deep2Lead: A distributed deep learning application for small molecule lead optimization},
  author = {Tarun Kumar Chawdhury and David J. Grant and Hyun Yong Jin},
  journal= {arXiv preprint arXiv:2108.05183},
  year   = {2021}
}

Comments

6 Pages, 1 figure, 2 images

R2 v1 2026-06-24T05:01:43.291Z