James C. Sacchettini

This paper evaluates active learning strategies for whole-cell antibiotic discovery, finding an optimal approach that significantly improves hit rates and generalizability across bacterial species.

This study identifies cleavage requirements and specificities of mycobacterial RNase E using in vitro assays, showing substrate length, 5' phosphate preference, and cleavage position dependencies.

This study identifies MutT4 in Mycobacterium tuberculosis as the RppH homolog, showing it forms condensates that facilitate mRNA degradation and enhance stress resistance.

Fleming is an AI agent that identifies lead compounds for Mycobacterium tuberculosis by combining discriminative and generative models, achieving higher discrimination and hit rates than alternative approaches.