Molecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg 431 83, Sweden.
Structure & Biophysics, Discovery Sciences, R&D, AstraZeneca, Cambridge CB2 8PA, UK.
Bioinformatics. 2022 Oct 31;38(21):4951-4952. doi: 10.1093/bioinformatics/btac614.
We present Icolos, a workflow manager written in Python as a tool for automating complex structure-based workflows for drug design. Icolos can be used as a standalone tool, for example in virtual screening campaigns, or can be used in conjunction with deep learning-based molecular generation facilitated for example by REINVENT, a previously published molecular de novo design package. In this publication, we focus on the internal structure and general capabilities of Icolos, using molecular docking experiments as an illustrative example.
The source code is freely available at https://github.com/MolecularAI/Icolos under the Apache 2.0 license. Tutorial notebooks containing minimal working examples can be found at https://github.com/MolecularAI/IcolosCommunity.
Supplementary data are available at Bioinformatics online.
我们介绍了 Icolos，这是一个用 Python 编写的工作流管理器，可作为用于自动化药物设计结构基础复杂工作流的工具。Icolos 可以用作独立工具，例如在虚拟筛选活动中，或者可以与基于深度学习的分子生成结合使用，例如由之前发布的分子从头设计包 REINVENT 提供支持。在本出版物中，我们重点介绍了 Icolos 的内部结构和一般功能，使用分子对接实验作为说明性示例。
源代码可在 https://github.com/MolecularAI/Icolos 上免费获得，遵循 Apache 2.0 许可证。包含最小工作示例的教程笔记本可在 https://github.com/MolecularAI/IcolosCommunity 上找到。
补充数据可在生物信息学在线获得。
