  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 3D-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. Besides, we experimentally test our method
in real-world applications, showing that it can successfully generate valid
linkers conditioned on target protein pockets.
