Engineered proteins have strongly benefited the effectiveness and variety of precision drugs, molecular diagnostic agents, and fundamental research reagents. A growing demand for new therapeutics motivates the innovative use of natural proteins – improving upon their native properties – as well as discovering proteins with entirely new functionality. Importantly, these are fundamentally separate goals. While evolving improved function can result from making a few carefully chosen mutations, discovering novel function often requires giant leaps to be taken in protein sequence space. Discovering novel function is a notoriously challenging task. The immensity of sequence space (e.g. proteins of length n have 20^n unique options) makes it essentially impossible to experimentally or computationally test all possible protein sequences. Within this space, the landscape is incredibly barren and rugged (i.e. most sequences lack function entirely and making small changes to a protein often damage the activity). Rather than randomly mutating a protein, combinatorial protein libraries provide a systematic and efficient approach for searching sequence space. This method offers precise control over which protein sites are mutated and which amino acids are allowed at the diversified sites. To improve the likelihood of sampling useful sequences, numerous techniques can elucidate the structure-function relationships in proteins. Generally, these techniques have not been applied to combinatorial library design; however, we propose that some, or all, could be greatly beneficial in this area. In this thesis work, protein libraries are designed for the purpose of discovering high affinity, specific binders to a collection of interesting targets. High-throughput sequencing of evolved binders, natural protein-protein interface composition, structural assessment, and computational analysis of stability upon mutation collectively informed sitewise library designs – residues predicted to support function were allowed but destabilizing residues or those not likely to benefit function were avoided. We use multiple small protein scaffolds (affibody and fibronectin) as model systems to test the hypothesis that constrained sitewise diversity will improve the efficiency of novel protein discovery. This hypothesis was experimentally supported by a direct comparison of high-affinity ligand discovery between the sitewise constrained library and a uniformly diversified library (i.e. allowing all 20 residues at each diversified site). The constrained library showed a 13-fold improved likelihood of binder discovery. Moreover, the constrained library variants demonstrated superior thermal stability (Tm 15 °C higher than unbiased variants). This work provides further evidence that sitewise diversification of protein scaffolds can improve the overall quality of combinatorial libraries by offering broad coverage of sequence space without sacrificing stability.
University of Minnesota Ph.D. dissertation. April 2017. Major: Chemical Engineering. Advisor: Benjamin Hackel. 1 computer file (PDF); x, 191 pages.
Constrained Diversification Enhances Protein Ligand Discovery and Evolution.
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