Generation of dual-target compounds using a transformer chemical language model
Srinivasan and Bajorath report transformer-based chemical language models for the generation of compounds with defined activity against unrelated targets. Using a new cross-fine-tuning technique, model variants are optimized for the design task by applying molecular similarity constraints; fine-tuned models chart relevant chemical space and exactly reproduce known dual-target compounds.