Ligand-based drug design aims to identify novel drug candidates of similar
shapes with known active molecules. In this paper, we formulated an in silico
shape-conditioned molecule generation problem to generate 3D molecule
structures conditioned on the shape of a given molecule. To address this
problem, we developed a translation- and rotation-equivariant shape-guided
generative model ShapeMol. ShapeMol consists of an equivariant shape encoder
that maps molecular surface shapes into latent embeddings, and an equivariant
diffusion model that generates 3D molecules based on these embeddings.
Experimental results show that ShapeMol can generate novel, diverse, drug-like
molecules that retain 3D molecular shapes similar to the given shape condition.
These results demonstrate the potential of ShapeMol in designing drug
candidates of desired 3D shapes binding to protein target pockets.

该研究旨在利用基于配体的药物设计方法，根据已知活性分子的相似形状，寻找新的药物候选化合物。通过开发一种称为 ShapeMol 的新型生成模型，该模型可以根据给定分子的形状生成 3D 分子结构。实验结果表明，ShapeMol 可以生成与给定形状条件相似的新型多样化的类似药物的分子，展示了 ShapeMol 在设计与蛋白靶点结合的具有期望的 3D 形状的药物候选化合物方面的潜力。