  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.
