About This Project
Chemical deconstruction of plastics is a key strategy for fighting waste accumulation and increasing recycling viability. In recent years, enzymes have been discovered that can degrade the plastic polyethylene terephthalate (PET), but the natural enzymes (PETases) unravel at the elevated temperatures required for efficient PET degradation. We aim to design PETases using new generative AI-based methods, to deliver ultrastable, efficient plastic degrading enzmyes.
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What is the context of this research?
Chemical deconstruction (1) of plastic is an attractive solution to the plastic accumulation problem (2). Enzymatic deconstruction of the plastic polyethylene terephthalate (PET) has gained significant traction in recent years after the discovery of PET degrading organisms (3, 4). However, optimal enzymatic PET hydrolysis requires high temperatures, which allows penetration of the enzyme into the rigid plastic (5). Natural enzymes are not evolved to operate at these temperatures, limiting their activity. Further, current studies have only focused on several structurally related enzymes (4).
Ultimately, a broader exploration of sequence, structure, and mechanistic space might yield PET degrading enzymes that meet the requirements for process-scale plastic chemical recycling.
What is the significance of this project?
Enzymes that depolymerize PET (PETases) have been discovered, but their thermal stability and catalytic efficiency have limited their applicability (4). Further, different plastic formulations and compositions have differing reactivity profiles between PETases (5). Systematic understanding of the structure function relationships in PET deconstruction will be crucial for engineering efficient PETases.
Computational protein design tools have been applied to PETases (6) with the goal of increasing their thermal stability. Ground-up de novo protein design (7) could instead deliver ultrastable PETases. Emerging AI-generative models of protein design (8) and active site design (9) have revolutionized the field and could enable first-in-class enzymes with entirely new structures and mechanisms.
What are the goals of the project?
AI-based protein design will be combined with rational protein engineering and high-throughput evolution in order to arrive at novel, ultrastable, highly active PETases.
High thermal stability:
·Tm > 90 °C (5)
·14-day half-life at 80 °C (5)
Amenable to different post-consumer waste products:
·Operates on bulk material (i.e. water bottle)
·Operates on crystalline and semicrystalline PET
·Selectively deconstruct PET in mixed plastic samples
·kcat/kM > 2x104 M-1 s-1 (10)
Beyond these goals, new structures and mechanisms for PET deconstruction will inform further engineering endeavors.
Oct 19, 2023
Meet the Team
The DeGrado lab is a diverse group of protein designers, biologists, and chemists with a wide range of experience in protein engineering and molecular biology.
I aim to innovate sustainable chemistry processes by combining modern synthetic organic chemistry with computational protein design. A New Jersey native, I studied chemistry and biochemistry at Rowan University which built my passion for understanding fundamental reaction mechanisms. During my graduate studies at UC Berkeley, I studied natural product total synthesis, where I became acquainted with the ability of nature to build amazing molecular architectures. Through my studies I gained expertise in synthetic organic chemistry, but also witnessed the shortcomings and waste of traditional chemistry processes. From my time there, it became clear to me that the future of chemistry would involve using biological tools to enable green chemistry processes.
These experiences led me to join the lab of Bill DeGrado at UC San Francisco as a postdoctoral scholar to study the computational design of proteins. Bill is an expert in the field, having coined the term de novo protein design and contributed several landmark discoveries. Here, I am using tools including AI and machine learning to design proteins that catalyze new-to-nature reactions. The combination of these training experiences uniquely positions me to design biocatalysts that can catalyze the sustainable synthesis of drug molecules, act as next-generation energy devices, and remove waste from the environment.
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