Harnessing Genomic Information to Engineer Combinatorial Biosynthesis of a Large Polyketide Natural Products Library

Abstract Natural products have outstanding pharmaceutical pedigree approximately of FDA approved small molecule drugs are derived from plant bacterial or fungal sources To discover new natural products Warp Drive Bio has assembled an enormous proprietary and searchable database of microbial genomes and biosynthetic gene clusters To date our database comprises genomes sequenced encoding the biosynthesis of million natural compounds Over the course of our genome mining campaign we identified WDB a cyclic polyketide synthase PKS natural product by a search for biosynthetic clusters related to FK and Rapamycin Both FK and Rapamycin target important signaling pathways with high potency and selectivity and these compounds have entered the clinic with annual sales of $ billion We propose to force the evolution of this clinically relevant family of natural products by applying combinatorial biosynthesis techniques to create a library of new WDB analogs The innovation described here represents an integrated platform for the combinatorial biosynthesis of polyketides on an industrial scale We built a prediction algorithm for the engineering of novel PKS clusters by analyzing our vast genomic inventory of PKS natural products Second we developed a robust genetic assembly methodology to construct of a chemically diverse PKS library of WDB analogs and we expressed the library in an optimized Streptomyces host Third we have developed two mass spectrometry assays based on FKBP binding that allow the precise identification of WDB analogs and a FKBP affinity proteomics LC MS assay to identify the protein targets of WDB analogs in human lysates The goal of this proposal is to assess the feasibility of large scale evolvalog generation by performing a detailed analysis of a member evolvalog library In Aim we propose to analyze the library by mass spectrometry to determine if the engineered clusters produce novel evolvalogs In parallel we will assess the genetic identity of each evolvalog expression construct by next generation sequencing By linking the identity of module module combinations to successful polyketide production we can refine our module swapping algorithm to increase the success rate for new library designs based on high value PKS clusters In Aim we will map the human protein targets of evolvalogs by a target ID assay to understand the rules by which polyketide engineering can reprogram target engagement in human proteome These data will accelerate the rational design of polyketide combinatorial libraries with novel target profiles thus yielding a direct path to diverse polyketide natural product libraries for drug discovery Using multiple bioinformatic methods and a robust genetic assembly methodology we have assembled a member natural products library to experimentally assess and computationally optimize polyketide combinatorial biosynthesis in hopes of identifying novel therapeutics to treat infections and other diseases