Microsoft Research AI4Science, UK. Electronic address: https://twitter.com/@megjanestanley.
Microsoft Research AI4Science, UK.
Curr Opin Struct Biol. 2023 Oct;82:102658. doi: 10.1016/j.sbi.2023.102658. Epub 2023 Jul 18.
Computational techniques, including virtual screening, de novo design, and generative models, play an increasing role in expediting DMTA cycles for modern molecular discovery. However, computationally proposed molecules must be synthetically feasible for laboratory testing. In this perspective, we offer a succinct introduction to the subject, and showcase typical workflows to integrate synthesis planning, synthesizability scoring, and molecule generation. Finally, we address limitations and opportunities for future research.
计算技术,包括虚拟筛选、从头设计和生成模型,在加速现代分子发现的 DMTA 循环方面发挥着越来越重要的作用。然而,计算提出的分子必须在合成上可行,才能进行实验室测试。在这个观点中,我们提供了一个简洁的介绍,并展示了典型的工作流程,以整合合成规划、可合成性评分和分子生成。最后,我们讨论了未来研究的局限性和机会。