A strategy to rationally design and systematically optimize polymers for the efficient delivery of specific therapeutics is highly needed. The combinatorial polymer library approach could be an effective way to this end. The post-polymerization modification of reactive polymer precursors is applicable for the combinatorial synthesis of a library of functional polymers with distinct structural diversity across a consistent degree of polymerization. This allows for parallel comparison and systematic evaluation/optimization of functional polymers for efficient therapeutic delivery. This review summarizes the key elements of this combinatorial polymer synthesis approach realized by post-polymerization modification of reactive polymer precursors towards the development and identification of optimal polymers for the efficient delivery of therapeutic agents.

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RNA Polymerase I(Pol I) is one of three essential DNA dependent RNA polymerases in eukaryotes and is responsible for synthesizing ribosomal RNA. A critical and essential Pol I transcription factor in yeast is Core Factor (CF) which binds to a ~24 bp region in the rDNA promoter called the Core Element (CE). CF plays fundamental roles in the Pol I transcription process helping to recruit Pol I and open Pol I promoter DNA before initiation. Previously, it was not yet known how CF precisely recognized the CE. When interacting with DNA, proteins use two main mechanisms: i) base‐pair readout, and ii) shape/structural readout. Base‐readout is the most common and is dominated by hydrogen bonding between the amino acid residues and base‐pair hydrogen bond donors and acceptors. The second mechanism centers around DNA shape readout where proteins target specific DNA features such as curvature, bendability, and groove width. Previous studies from our lab have shown that CF and its human orthologue, Selectivity Factor 1 (SL1), use an evolutionarily conserved mechanism to target DNA which is governed by interactions with the GC minor groove, a unique surface rarely targeted by DNA‐binding proteins. To further understand the extent of structural recognition as well as specific DNA features CF may be using to interact with CE, we have employed a variety of selection‐based methods to resolve the structural rules governing CF’s interaction with DNA. Our findings are consistent with a model that CF‐CE interaction is governed primarily by DNA shape‐based structural features rather than sequence.