Collaborative Research: SusChEM: Unlocking the fundamental mechanisms that underlie selectivity in oleochemical producing enzymes

Project: Research project

Project Details


Engineering, mathematics, biochemistry, and biology are combined to develop strategies for converting renewable resources into higher-value chemicals and materials. Some of these products have never been produced biologically, so organisms need to be modified to make this possible. There is also a great need for computational tools that can predict beneficial modifications to cellular proteins, thereby guiding these efforts. This research project is developing novel proteins that are active in the sustainable production of fats and oils. If successful, this work has the potential to displace unsustainable and environmentally unfriendly processes that contribute to the deforestation of tropical regions. Research experiences for undergraduate students and outreach efforts directed at K-12 students and the public through the SCIENCountErs program are being provided and serve to enhance the development of a highly knowledgeable STEM workforce. The efforts are enhancing our understanding of the techniques, capabilities, and limitations of protein design.

In this collaborative research project, researchers are integrating computational and experimental methods to develop software that will be used to design novel enzymes involved in oleochemical metabolism. This protein-design infrastructure is integrating recent developments in molecular modeling and machine learning and developing design rules for tailoring chain length specificity for three oleochemical-synthesizing enzymes. These novel enzymes are being deployed in microbial biocatalysts and evaluated for their ability to produce oleochemicals from renewable resources. Upon conclusion, this work will generate a deeper understanding of selectivity in oleochemical metabolism, novel enzymes and microbial biocatalysts for producing specialty oleochemicals, and enzyme-design capabilities that could be widely applied in synthetic biology applications.

Effective start/end date9/1/178/31/21


  • National Science Foundation: $300,000.00


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