Project Details

Description

0967062

Maranas

Enzymes are versatile structures tuned by nature to selectively carry on a vast array of catalytic functions. Their potential to provide solutions to challenges in biomass treatment, biofuels production, biosensing, wastewater and environmental pollutants treatment has long been recognized. However, many of these enzymes suffer from poor stability under the desired reaction conditions, or have inadequate catalytic activity, or a lack of specificity for non-native substrate molecules. The rational design of enzymes for improved or novel catalytic activity remains an open challenge because catalytic efficiency depends on the nature of the molecules to be reacted, and reflects a balance of active site access and binding with improved transition state stabilization. High throughput experimentation will not work here due to the difficulty and cost of screening and the enormity of the combinatorial design space.

The trio of PIs, Costas Maranas, Patrick Cirino and Michael Janik, all at Pennsylvania State University, seek to address these shortcomings in a systematic fashion, by first developing a multi-scale computational work-flow to design enzymes for improved activity and specificity and then experimentally validating the computational redesign of the enzymes. Ultimately the methodology will be used to design mutant P450 BM-3 monooxygenase enzymes which are functionally expressed at high levels in E. coli and are used for hydroxylation of small alkanes for alcoholic biofuels. Their target substrates are ethane and propane, with methane the ultimate goal.

The most far-reaching results for this program would be to devise an enzyme that works on methane to produce methanol. Even the development of enzymes capable of rapid and selective oxidation of C1-C3 alkanes could aid in the efficient utilization of remote gas resources or low value refinery gas streams for fuel and chemical generation. The potential is for a new integrated paradigm for enzyme redesign where hypotheses generated by the computational workflow are used to guide the experiment and experimental results serve to correct and complete the computational base.

The educational and outreach efforts will couple the REU approach with attempts to use existing University programs titled SROP, WISER and MURI, all of which are research ?based programs to inspire women and minorities to experience engineering research early in their careers. The PIs plan to include this work in Penn State?s program titled International Genetically Engineered Machines, or IGEM. This program targets high school and undergraduates with hands-on exposure to synthetic biology.

StatusFinished
Effective start/end date7/15/106/30/14

Funding

  • National Science Foundation: $394,905.00

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