A Reductive Dehalogenase for Aerobic Applications In the Environment

含有氯或氟的有机化合物（卤化物）非常难以降解。 为了改善它们的降解，研究人员将修改一种酶，这种酶表现出正确的能力，但目前缺乏识别这些污染物的能力。 卤代酚将是所使用的模型化合物。如果成功的话，这种方法将能够消除以前发现不可能处理的化合物的污染。研究生将学习联合收割机结合实验和理论方法来产生新的酶。 本科生将帮助设计酶使用教育游戏来模拟蛋白质折叠和构象。将积极招募代表性不足的少数民族参与项目的各个方面。从我们的环境中去除卤代苯酚污染物的方法是可行的，但不令人满意。 强化学氧化剂可用于废水，但其残留物会对下游工艺产生不利影响。 或者，可以使用生物降解卤代酚，但它们需要厌氧条件。 相比之下，碘酪氨酸脱碘酶具有使用与大气氧独特相容的还原过程降解卤代苯酚的潜力。 这种酶的一些天然例子已经过研究，但都是酪氨酸衍生物的特异性。 因此，我们的目标是开发接受更广泛底物的新变体。 三个并行的计算方法将进行测试，预测必要的突变，以产生稳定的酶与活性位点的几何形状有利于卤代苯酚底物。 将表达最高等级的变体并筛选所需活性。 进一步的优化将依赖于使用随机诱变和基因改组方法的定向进化。 这项研究工作应确定一个一般的方法，用于调节活性部位的盖子，以适应选定的基板，除了提供一个可测试的产品，工程酶卤代酚decontamination.This奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.