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

Autor:	Chawdhury, Tarun Kumar, Grant, David J., Jin, Hyun Yong
Rok vydání:	2021
Předmět:	Quantitative Biology - Quantitative Methods Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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. Comment: 6 Pages, 1 figure, 2 images
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2108.05183 Zobrazit plný text záznamu View this record from Arxiv