Intrinsically Disordered Protein Polymer Libraries as Tools to Understand Protein Hydrophobicity

Abstract

<p>Intrinsically disordered protein polymers (IDPPs) are repetitive biopolymers that, when enriched with prolines, glycines, and aliphatic amino acids, have observable lower critical solution temperature (LCST) phase transition behavior at physiologically relevant temperature and concentration ranges. This behavior is a striking feature of disordered proteins in nature, where chemical or physical stimuli lead to sharp conformational or phase transitions. Accordingly, protein-based polymers have been designed to mimic these behaviors, leading to a broad range of biotechnological applications. This work is driven by two approaches. In our science focused approach, we developed a polymer-physics based framework for understanding IDPP hydrophobicity using the relationship between phase transition temperature and globule surface tension. This physics-based framework has allowed us to better understand the unified contributions of chain length, concentration, temperature, and individual amino acid side chains to IDPP hydrophobicity by studying phase transition data. In our engineering focused approach, we developed novel tools that enable the high throughput discovery of new proteins that exhibit phase transitions, in order to increase the number of known stimuli responsive peptide sequence motifs beyond the limits of bioinspired design. The exhaustive discovery of new proteins that exhibit phase transitions consists of gene synthesis and protein screening. We developed two key technologies that has enabled (1) the scalable synthesis of repetitive gene libraries using a novel graph theoretic gene optimization approach (Codon Scrambling) and (2) the pooled synthesis of large complex gene libraries from libraries of oligonucleotides. Combined with pipelines for the screening of phase transition behavior, these technologies have enabled us to generate a diverse library of protein sequences necessary to validate our theoretical models. Finally, we developed an algorithm for the de novo design of nonrepetitive protein sequences that exhibit phase transition behavior, further broadening the sequence space of stimuli responsive synthetic IDPPs.</p>