Ideas lab: usprd: AI-designed enzymes using non-natural cofactors for the production of BIO-based acrylates

The National Science Foundation (NSF) has awarded a $2,233,515 Cooperative Agreement to Arzeda Corp under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program. The project aims to transform the production of acrylates, which are high-value chemical components used in products like paints and plastics, by leveraging artificial intelligence (AI)-driven biotechnology. The team will engineer enzymes to utilize non-natural cofactors, enabling a scalable, cost-effective, and cell-free biocatalytic process to convert affordable plant material into bio-based acrylates. Key objectives include demonstrating the complete production process at pilot scales, training a new workforce in protein design and synthetic biology, and advancing cell-free biocatalysis capabilities. This project builds on Arzeda's expertise in AI-driven enzyme design and synthetic biology, as well as the company's prior federal grants and contracts focused on developing innovative enzymatic solutions for sustainable chemical production and national defense applications.

Abstract

AI-designed enzymes using non-natural cofactors for the production of BIO-based acrylates the project aims to transform the production of molecules known as acrylates with artificial intelligence (AI)-driven biotechnology. Acrylates are expensive components of paints, plexiglas?, and super-absorbent materials. By using engineered enzymes and innovative, low-cost chemicals, the process will convert affordable plant material into these high-value products instead. The team of experts from academia and industry will test this technology at pilot scales, demonstrating its potential to strengthen the U.S. Bioeconomy. The project will also train a new workforce in protein design and synthetic biology. This project leverages artificial intelligence and advanced protein engineering to develop a scalable, cost-effective, and cell-free biocatalytic process for producing methylene butyrolactone (MBL), a BIO-based acrylate monomer. The work begins with mining and redesigning natural enzymes to catalyze the conversion of itaconate to MBL using machine learning-guided frameworks and high-throughput design-build-test-learn cycles. Enzymes will be further engineered to utilize a non-natural cofactor, which provides enhanced stability, cost efficiency, and suitability for industrial conditions while overcoming traditional biochemical limitations. Subsequent phases involve strain engineering for enzyme production at titers exceeding 1 G/L in E. Coli and demonstrating the complete process in 1-5L bioreactors. By coupling enzymes with chemical conversion processes, the project integrates enzyme performance, cofactor recycling, and chemical efficiency to achieve over 90% yield at industrial scales. Beyond enabling cost-competitive MBL production, this project overcomes key limitations of natural cofactor-dependent enzymes, advancing cell-free biocatalysis and its broader applications in synthetic pathways. The resulting platform will drive innovation across the bioeconomy, transforming industrial biotechnology through enhanced scalability and efficiency. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are planned for this award.