Lead optimisation is the phase of a drug development program where promising compounds undergo slight modifications with the aim of improving selected properties whilst maintaining other favourable properties. Despite recent interest in computational methods which claim to be able to facilitate de-novo generation of molecules with desirable properties, such methods have yet to be widely deployed in lead-optimisation programs. Most in-silico generative processes perform constrained optimisation by generating molecules with a high Tanimoto similarity with the original molecule, meaning that important functional groups can be modified. I am working to develop a fragment-growing model which will keep the original fragment fixed and incorporate important protein-specific information, with the aim of generating a lead optimisation tool which can be used by medicinal chemists to suggest modifications to a lead.