Organic compounds that contain chlorine or fluorine (halogenates), are remarkably difficult to degrade. To improve their degradation, the investigators will modify an enzyme that demonstrates the correct capability but currently lacks the ability to recognize these pollutants. Halogenated phenols will be the model compounds used. If successful, this approach will enable the decontamination of compounds previously found impossible to treat. Graduate students will learn to combine experimental and theoretical approaches to generate new enzymes. Undergraduate students will help design enzymes using an educational game to simulate protein folding and conformation. Underrepresented minorities will be actively recruited to participate in every aspect of the project.

Methods for removing halophenol contaminants from our environment are available but unsatisfactory. Strong chemical oxidants can be used in waste water but their residue adversely affects downstream processes. Alternatively, organisms can be used degrade the halophenols, but they require anaerobic conditions. In contrast, the enzyme iodotyrosine deiodinase has the potential to degrade halophenol using a reductive process that is uniquely compatible with atmospheric oxygen. A number of natural examples of this enzyme have been examined, but all are specific for tyrosine derivatives. Consequently, our goal is to develop new variants that accept a broader range of substrates. Three parallel computational approaches will be tested for predicting the necessary mutations to generate stable enzymes with active site geometries favoring halophenol substrates. The highest ranked variants will be expressed and screened for the desired activity. Further optimization will rely on directed evolution using methods of random mutagenesis and gene shuffling. This research effort should define a general approach for modulating active site lids to accommodate chosen substrates in addition to providing a testable product, engineered enzymes for halophenol decontamination.

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.

Project Start
Project End
Budget Start
2018-09-01
Budget End
2021-08-31
Support Year
Fiscal Year
2018
Total Cost
$471,231
Indirect Cost
Name
Johns Hopkins University
Department
Type
DUNS #
City
Baltimore
State
MD
Country
United States
Zip Code
21218