Ecology-inspired & genomics-assisted discovery of bioactive natural products

Bacteria biosynthesize structurally diverse small molecules to interact with their environment. Many of the complex natural products involved in this “metabolic small talk” have been exploited as drugs in human and veterinary medicine.
Genome mining, i.e., the screening of genome sequences for their natural product biosynthetic potential, has revolutionized natural product discovery. Several generations of highly so-phisticated genome mining pipelines have been developed for the identification and annotation of natural product biosynthetic blueprints in genome sequences and to predict the structures of the associated metabolites.

Most genome mining pipelines are based on the seemingly universal biosynthetic principles deciphered for each natural product class. Natural products whose biosynthesis deviates from these seemingly universal rules, however, are in many cases overlooked by state-of-the-art genome mining algorithms. The corresponding non-canonical biosynthetic blueprints display an almost untapped treasure map for the identification of novel bioactive metabolites.
We develop artificial intelligence-based genome mining algorithms to chart this biosynthetic dark matter and to identify putative non-canonical biosynthetic transformations with the goal to expand natural product chemical space.

THURSDAY  I  FEB. 24  I  3:30-4:30 PM CST  I  REMOTE SEMINAR