Natural Products Discovery Core

A first-in-class library of natural product extracts, as well as characterization and transformational tools and expertise for basic biology and drug discovery projects.

Roughly half of the drugs in clinical use today started as natural products — molecules that evolved inside microorganisms and plants that form the backbone of antibiotics, anti-cancer agents and other medicines.

Over the past decade, the University of Michigan has become a leader in natural product sciences. 

The LSI's Natural Products Discovery Core has developed a 45,000-sample (and growing) library of natural product extracts derived from a unique collection of diverse marine and terrestrial actinomycetes, fungi and cyanobacteria. The core provides researchers at U-M and external partners with the technology and expertise to develop candidates identified through high-throughput screening into unique, bioactive, patentable, small molecules.

Rapid genomic and metabolomic profiling allows users to identify high value molecules as probes and drug leads.

Recent investments by the U-M Biosciences Initiative will add state-of-the art mass spectrometry and NMR resources for structure elucidation, as well as the recruitment of new faculty and specialists.


Nirmal Chaudhary, Ph.D. has joined the NPDC team. Nirmal brings years of experience in analytical chemistry, synthetic chemistry, chemical biology and drug discovery. He also brings his knowledge in data acquisition and interpretation, and troubleshooting abilities on key instruments. Welcome Nirmal!

Our Services

More than 45,000 natural product extracts collected around the globe. Available for high-throughput screening in the U-M Center for Chemical Genomics.
Bioactive molecule identification using traditional bio-assay guided fractionation, as well as new data-guided discovery tools. Small-molecule structural characterization. Optimization for creating intellectual property.
Biocatalytic Discovery
Ability to do high-throughput molecular characterization of enzymatic products, and analysis using rapid separation technologies.
Biosynthetic cluster mining of microbial genomic DNA. Artificial-intelligence & machine learning-based genome-to-natural-product technologies.