Drug design is a crucial step in the drug discovery cycle. Recently, various deep learning-based methods design drugs by generating novel molecules from scratch, avoiding traversing large-scale drug libraries. However, they depend on scarce experimental data or time-consuming docking simulation, leading to overfitting issues with limited training data and slow generation speed. In this study, we propose the zero-shot drug design method DESERT (Drug dEsign by SkEtching and geneRaTing). Specifically, DESERT splits the design process into two stages: sketching and generating, and bridges them with the molecular shape. The two-stage fashion enables our method to utilize the large-scale molecular database to reduce the need for experimental data and docking simulation. Experiments show that DESERT achieves a new state-of-the-art at a fast speed.
翻译:药物设计是药物发现周期的关键一步。最近,各种深层次的基于学习的方法设计药物,从零开始生成新分子,避免了大型药物图书馆的横跨。然而,它们依赖稀缺的实验数据或耗时的对接模拟,导致问题过于适应有限的培训数据和缓慢的生成速度。在本研究中,我们建议采用零射药物设计方法DESERT(SkEtching和基因RaTing的药物标识 ) 。 具体地说,DESERT将设计过程分为两个阶段:草图和生成,以及将其与分子形状连接起来。两阶段方式使我们能够利用大型分子数据库减少对实验数据和对接模拟的需求。实验表明DESERT以快速的速度实现了新的工艺状态。