Many bona fide cancer targets involve intracellular protein-protein interactions that are currently considered undruggable. Increasingly, peptide libraries are serving as storehouses for identifying inhibitors for these targets. One advantage of peptides is that libraries of enormous diversity (trillions of unique peptides) can be created using in vitro translation. This extreme diversity dramatically enhances the ability to find a lead. But, these libraries are limited to 20 amino acid monomers, and this means that one needs to create long peptides (>10 amino acids) in order to access the full diversity. Peptides of this length are very large and polar in comparison with the collection of orally bioavailable peptide drugs. The molecular weight of these libraries could be reduced without sacrificing diversity if the number of building blocks at each position could be increased. The chief aim of this proposal, therefore, is to grow the number of building blocks usable by in vitro translation from 20 to 30. This will be achieved by breaking the degeneracy of the genetic code using isolated, native E. coli tRNAs. First, a novel fluorous capture method will be developed that can be used to selectively isolate any given tRNA species from E. coli total tRNA. Second, these tRNAs will be analyzed for their codon readthrough preferences using a library of mRNAs and an in vitro selection strategy which will enable simultaneous readthrough measurements of all 64 codons in one tube. tRNAs bearing amino acids of unique masses will then be used together with a mRNA containing each codon in order to measure the extent to which the genetic code can be expanded. Once completed, this work will enable access to improved peptide libraries which pack more diversity elements in each position. When coupled with methods to introduce cyclic constraints and modified amino acids, these improved libraries will serve as exciting collections for the discovery of lead inhibitors of undruggable cancer targets.
The work described in this proposal will improve access to short, yet extremely diverse peptide libraries. This new technology will ultimately improve the drug discovery process for difficult cancer targets.
