Joseph P. Sheehan

This paper develops a machine learning pipeline to discover novel antibacterial compounds with distinct mechanisms of action, finding that training data bias limits the discovery of mechanistically novel antibiotics.

This study tracks ribosome-sized particles in E. coli to show that their 3D diffusion is influenced by macromolecular interactions and geometrical confinement, revealing sub-diffusive motion due to nucleoid and cell boundary constraints.