Predictive Minisci and P450 Late Stage Functionalization with Transfer Learning

Structural diversification of lead molecules is a key component of drug discovery to explore close-in chemical space. Late stage functionalizations (LSFs) are versatile methodologies capable of installing functional handles on richly decorated intermediates to deliver numerous diverse products in a single reaction. Predicting the regioselectivity of LSF is still an open challenge in the field. Numerous efforts from chemoinformatics and machine learning (ML) groups have made significant strides in this area. However, it is arduous to isolate and characterize the multitude of LSF products generated, limiting available data and hindering pure ML approaches.