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

DeepFrag: An Open-Source Browser App for Deep-Learning Lead Optimization.
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DOI:
10.1021/acs.jcim.1c00103
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发表时间:
2021-06-28
影响因子:
5.6
通讯作者:
Durrant JD
Durrant JD
中科院分区:
化学2区
文献类型:
--
作者:
Green H;Durrant JD

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先导化合物优化是早期药物发现的关键步骤,涉及对小分子配体进行化学修饰以改善结合亲和力等性质。我们最近开发了DeepFrag,这是一种能够推荐此类修改的深度学习模型。虽然DeepFrag是一个强大的假设生成工具,但它目前是用Python实现的,因此需要一定程度的计算专业知识。为了鼓励更广泛的采用,我们创建了DeepFrag浏览器应用程序,它提供了一个用户友好的图形用户界面,可以在用户的Web浏览器中运行DeepFrag模型。浏览器应用程序不需要用户将其分子结构上传到第三方服务器,也不需要单独安装任何第三方软件。我们希望该应用程序将成为研究人员和学生的有用工具。它可以免费访问,无需注册,在。源代码也可以在,根据开源Apache许可证2.0版的条款发布。
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.
DOI: 10.1111/j.1747-0285.2008.00761.x
发表时间: 2009-02
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