REINVENT 4 is a modern open-source generative AI framework for the design of small molecules. The software utilizes recurrent neural networks and transformer architectures to drive molecule generation. These generators are seamlessly embedded within the general machine learning optimization algorithms, transfer learning, reinforcement learning and curriculum learning. REINVENT 4 enables and facilitates de novo design, R-group replacement, library design, linker design, scaffold hopping and molecule optimization. This contribution gives an overview of the software and describes its design. Algorithms and their applications are discussed in detail. REINVENT 4 is a command line tool which reads a user configuration in either TOML or JSON format. The aim of this release is to provide reference implementations for some of the most common algorithms in AI based molecule generation. An additional goal with the release is to create a framework for education and future innovation in AI based molecular design. The software is available from https://github.com/MolecularAI/REINVENT4 and released under the permissive Apache 2.0 license. Scientific contribution. The software provides an open–source reference implementation for generative molecular design where the software is also being used in production to support in–house drug discovery projects. The publication of the most common machine learning algorithms in one code and full documentation thereof will increase transparency of AI and foster innovation, collaboration and education.

中文翻译：

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重塑 4：现代人工智能驱动的生成分子设计

REINVENT 4 是一个用于小分子设计的现代开源生成人工智能框架。该软件利用循环神经网络和变压器架构来驱动分子生成。这些生成器无缝嵌入通用机器学习优化算法、迁移学习、强化学习和课程学习中。REINVENT 4 支持并促进从头设计、R 基团替换、文库设计、接头设计、支架跳跃和分子优化。本贡献概述了该软件并描述了其设计。详细讨论了算法及其应用。REINVENT 4 是一个命令行工具，可以读取 TOML 或 JSON 格式的用户配置。此版本的目的是为基于人工智能的分子生成中一些最常见的算法提供参考实现。该版本的另一个目标是为基于人工智能的分子设计的教育和未来创新创建一个框架。该软件可从 https://github.com/MolecularAI/REINVENT4 获取，并根据 Apache 2.0 许可发布。科学贡献。该软件为生成分子设计提供了开源参考实现，该软件还用于生产以支持内部药物发现项目。以一种代码形式发布最常见的机器学习算法及其完整文档将提高人工智能的透明度，并促进创新、协作和教育。