Seminars

Frontline malaria therapies are increasingly threatened by drug resistance, creating an urgent need for novel medicines. New strategies to discover antimalarial molecules are essential for sustaining a robust drug pipeline. Using experimental screening data from a small, curated compound library, we developed a machine learning model that predicts compounds active against a high-priority antimalarial drug target. This approach enables virtual screening of chemical space and prioritization of promising candidates for experimental validation.

The gut microbiota plays critical roles in human health, with numerous diseases linked to microbiota disruption. Intestinal mucus, which is composed primarily of mucin glycoproteins, provides a habitat and nutritional substrate for much of the microbiota, although its role in driving microbiota composition is still poorly understood. By culturing complex intestinal communities with or without mucin, we identified core health-associated bacteria enriched by mucin, with mucin architecture playing a key role in this enrichment.