Notice Number (NOT-OD-09-058) NIH Announces the Availability of Recovery Act Funds for Competitive Revision Applications Natural products are still the majority of therapeutic agents. However, they suffer from a difficulty in the creation of derivatives, and they can also be hard to supply. Derivatives are extremely important in the optimization of properties, such as toxicity or solubility that are critical to development of therapeutics. Recently, it has become increasingly popular to create libraries of derivatives using genetic engineering of natural product biosynthetic genes. Even in the best libraries, the numbers of derivatives are in the hundreds or low thousands. Recently, we discovered an evolutionary pathway that could potentially be harvested to generate tens of billions of derivatives. The compounds can be """"""""evolved"""""""" by directly challenging producing E. coli with different new environments. We hope to develop a system in which new activities can be pharmacologically optimized in a matter of days to weeks, exploring a huge diversity of unnatural natural products. To fully harness this unusual evolutionary property for application to human health needs, in this revision we propose to: 1) Characterize the chemical output of the ~8 million-scale library. We will determine whether there are any limits on the chemical output of this natural products biosynthetic pathway. 2) Apply assays that explore protein-protein interactions, antibiotic activity, and diagnostic capability of this library. We will test the suitability of these """"""""evolving"""""""" systems for broad and otherwise difficult target areas of therapeutic interest. 3) Optimize library compound expression and diversification. We will explore renewable expression and improve stable yields in E. coli. 4) Provide further pathway tools to add other post-translational modifications to the compounds. The suitability of new enzymes to library development will be explored.
We will harness recent scientific discoveries to therapeutic areas including antibiotics, protein interaction diseases, and diagnostics (such as for cancers and immune diseases). Compounds discovered will be rapidly optimized to advance drug leads for preclinical testing.
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