标题： Deep2Lead：一种用于小分子先导化合物优化的分布式深度学习应用 显示英文标题

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

摘要： 先导优化是药物发现中的关键步骤，以生成高效且选择性的化合物。 历史上，计算机虚拟筛选和基于结构的小分子设计促进了这些过程。 尽管深度学习在药物发现中的最近应用开启了其在计算机虚拟筛选的先导优化步骤的可能性，但由于工具可用性的限制，现实世界的应用仍然不足。 在这里，我们开发了一个单用户界面应用程序，称为Deep2Lead。 我们的基于网络的应用程序集成了VAE和DeepPurpose DTI，并允许用户在无需任何编程经验的情况下快速执行先导优化任务。 显示英文摘要

摘要： 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.