Natural products (NPs) and derivatives thereof provide a rich source of chemical matter for drug discovery and development. Over the past 30 years, NP-derived drugs have accounted for more than 35% of FDA approvals. Despite their demonstrated importance, development of new NPs has slowed over the past 15 years due to the lack of efficient methods for discovery, production, and optimization, coupled with the high rate of NP rediscovery using traditional bioassay-guided isolation techniques. Recently, next generation sequencing and genome-mining algorithms suggest that a wealth of uncharacterized natural products exist in Nature, revealing a vast untapped source of chemical diversity and biological activity. To unlock the latent potential of NPs predicted from genome-mining, our proposed Phase I study aims to develop an integrated high- throughput (HT) technology platform for rapidly (1) identifying, (2) synthesizing, and (3) screening new NPs. In Phase II, this technology platform will be automated with robotics to provide unprecedented speed and throughput for NP discovery and optimization. The utility of this integrated platform first will be demonstrated during Phase I using lasso peptides as a representative NP class. Lasso peptides are ribosomally synthesized and post translationally modified peptides (RiPPs) that display a unique folded topology that endows the compounds with extraordinary stability and a myriad of promising biological activities.
The aim of this proposal is to develop a platform that will significantly expand the known repertoire of lasso peptides, analogs, and targets. Genomic and metagenomic data mining will provide the sequence information required for HT generation of lasso peptides that will be screened for biological activity (initially antimicrobial). The proposed specific aims outlined below will be achieved through the collaboration between Genomatica, Inc. and Dr. Douglas Mitchell at the University of Illinois at Urbana-Champaign.
The proposed Phase I study aims to develop an integrated high-throughput technology platform for rapidly (1) identifying, (2) synthesizing, and (3) screening new natural products predicted from metagenomic data in order to unlock the latent potential of natural products.
