Fragment-based drug discovery has been an effective paradigm in early-stage drug development. An open challenge in this area is designing linkers between disconnected molecular fragments of interest to obtain chemically relevant candidate drug molecules. In this work, we propose DiffLinker, an E(3)-equivariant three-dimensional conditional diffusion model for molecular linker design. Given a set of disconnected fragments, our model places missing atoms in between and designs a molecule incorporating all the initial fragments. Unlike previous approaches that are only able to connect pairs of molecular fragments, our method can link an arbitrary number of fragments. Additionally, the model automatically determines the number of atoms in the linker and its attachment points to the input fragments. We demonstrate that DiffLinker outperforms other methods on the standard datasets, generating more diverse and synthetically accessible molecules. We experimentally test our method in real-world applications, showing that it can successfully generate valid linkers conditioned on target protein pockets.

基于片段的药物发现一直是早期药物开发的有效范例。该领域的一个公开挑战是设计断开的感兴趣分子片段之间的连接体，以获得化学相关的候选药物分子。在这项工作中，我们提出了 DiffLinker，一种用于分子连接体设计的 E(3) 等变三维条件扩散模型。给定一组不相连的片段，我们的模型将缺失的原子放置在它们之间，并设计一个包含所有初始片段的分子。与以前只能连接分子片段对的方法不同，我们的方法可以连接任意数量的片段。此外，模型会自动确定连接子中的原子数量及其与输入片段的连接点。我们证明 DiffLinker 在标准数据集上优于其他方法，生成更多样化且可合成的分子。我们在实际应用中对我们的方法进行了实验测试，表明它可以成功生成以目标蛋白袋为条件的有效接头。