Discipline: Biological Sciences
Subcategory: Materials Science
Session: 1
Room: Council
Hunter Hutson - Arizona State University
Co-Author(s): Logan Hessefort, Arizona State University, Tempe, AZ; Kyle Biegasiewicz, Arizona State University, Tempe, AZ; Timothy Long, Arizona State University, Tempe, AZ.
Polyurethane’s (PUR) is a ubiquitous class of polymers due to its modular physical properties and durability. The highly modular structure of polyurethanes allows for a range of applications from its pervasive use as a foam in tennis shoes and mattresses to its use in medical devices and specialty car parts as hard plastics. The durability of PURs makes them attractive as materials, however, this durability also decreases PURs lability towards depolymerization. Commonly groups are working towards chemical methods of depolymerization of PURs, mainly centering around glycolysis and ammonolysis, however, large-scale recycling of PUR is still limited to downcycling by shredding for carpet underlay. In an attempt to aid the development of a more circular economy for PURs we are working towards developing a biocatalyst capable of hydrolyzing the urethane carbonyl found in PURs, a polyurethanase (PURase). In this work, we believe implementing high-throughput screening methodologies such as multi-well microtiter plate readers and protein engineering techniques, such as rational design through molecular docking and molecular dynamics simulations we can develop a biocatalyst capable of mitigating PUR wastes abroad. Through the implementation of these methodologies and designed 96-well plate screens, including all variable controls, we have discovered an enzyme that can convert PUR model compounds into two major products. However, elucidation of the structure of these compounds is ongoing.
Funder Acknowledgement(s): National Science Foundation (NSF award #2132183)
Faculty Advisor: Logan Hessefort, kbiegasi@asu.edu
Role: Protein expression and purification (E.coli expression system, Ni-NTA chromatography), Molecular docking with model compounds using AutoDock Vina, Design of Experiments, low and medium throughput enzymatic screening (1.5 ml Eppendorf and 96-well microtiter plates), and data analysis.