About This Project
We propose a generative model to accomplish Programmable Enzymatic Degradation of plastics. The ultimate goal is to input a SMILES notation of any plastic, and return a novel functional enzyme sequence capable of degrading that plastic. Our model allows for de-novo design of enzymes for polymers without naturally occurring degradation enzymes, such as PP and PE. Resultant enzymatic “hits” will then undergo experimental validation to confirm their degradation efficacy.
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Join The DiscussionWhat is the context of this research?
Plastic has become a ubiquitous symbol of human advancement and paradoxically, our environmental shortcoming. The world produces over 300 million tons of plastic yearly, a figure that's steadily rising. Plastic pollution poses one of the most insidious threats to the environment and marine ecosystems. Originating from a variety of sources including single-use plastics, packaging, and discarded goods, these plastic pollutants persist in the environment for centuries, leaching harmful chemicals, exacerbating climate change, disrupting food chains, and physically harming aquatic life. Methods like recycling and waste management fall short due to economic, infrastructural, and scalability challenges. A transformative solution is essential—targeting plastics at their molecular level.
What is the significance of this project?
Nature's enzymes present a sustainable avenue to combat plastic pollution. Recent advances have seen progress in targeting polymers such as polyethylene terephthalate (PET), polyurethane (PUR), and polyamide (PA), with a total of 127 naturally-occuring degradation enzymes. However, these polymers account for only 14% of annual plastic waste. In stark contrast, polyethylene (PE) and polypropylene (PP), which represent a whopping 49% (193 million metric tons) of global plastic waste, are characterized by only four enzymes. Our focus must pivot to designing enzymes that degrade these polymers to truly make a dent in the plastic crisis. Therefore, we propose a generative model that designs novel enzymes tailored to degrade any plastic polymer, allowing us to degrade PP and PE.
What are the goals of the project?
Using deep learning and generative AI, we will:
Create a model in which we input any plastic’s polymer structure and design an enzyme able to degrade the respective plastic. This will allow us to design enzymes to degrade plastics, like PP, which has zero biochemically characterized degrading enzymes.
Curate a publicly available database of existing plastic structures and current/generated enzyme sequence pairs, along with information on the enzyme’s stability and degradation confidence score.
Create an experimental screening pipeline to validate our designed enzymes in the wet-lab.
Attaining these goals will lay the groundwork for a robust method to produce enzymes fit for degrading various plastics.
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Project Timeline
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Aug 01, 2024
Anticipated Project Completion
Meet the Team
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Team Bio
We are three motivated third-year undergraduates, joined by our study of Biomedical Engineering. We founded the Duke Applied Recycling Center (DARC) — the first small-scale recycling center designed to shred, melt, and mold single-use plastic waste into multi-use reusable products directly on a U.S. University Campus. We now leverage our unique BME/CompSci research experiences to form innovative solutions to tackle the plastic pandemic head on.
Rushil Yerrabelli
My passion lies at the interesection of biology and computer science. I have several years of experience in computational biology working in the lab of Dr. Jacques Banchereau at the Jackson Laboratory, and currently with Dr. Duygu Ucar, studying the immune system at different disease states. I am the Co-Founder and President of Duke Applied Recycling Center (DARC), the first on-campus plastic recycling center.
Srikar Kavirayuni
My passion lies at the intersection of Bio/AI Innovation, especially generative methods for biomolecular engineering. Currently, I work in the Programmable Biology Group, led by Dr. Pranam Chatterjee. Also work as the head of Research for Duke Applied Recycling Center.
Arnav Singh
My passion lies at the intersection of AI and Medicine. I am currently working with Dr. Amanda Randles, on developing a Deep Learning Computational Fluid Dynamics (CFD) model for the noninvasive diagnosis of Coronary Artery Disease (CAD). I am also the Co-Founder of Duke Applied Recyclin Center (DARC), the first on-campus plastic recycling center on a university campus in the United States.
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