A Reductive Dehalogenase for Aerobic Applications In the Environment

含有氯或氟的有机化合物(卤化物)很难降解。为了改善它们的降解，研究人员将修改一种酶，该酶显示出正确的能力，但目前缺乏识别这些污染物的能力。卤代酚将是使用的模型化合物。如果成功，这种方法将能够对以前发现无法处理的化合物进行净化。研究生将学习结合实验和理论方法来产生新的酶。本科生将使用一个模拟蛋白质折叠和构象的教育游戏来帮助设计酶。将积极招募代表性不足的少数群体参与该项目的各个方面。目前已有从我们的环境中消除卤酚污染物的方法，但并不令人满意。废水中可以使用强化学氧化剂，但其残留物会对下游工艺产生不利影响。或者，可以使用微生物来降解卤代酚，但它们需要厌氧条件。相比之下，碘酪氨酸脱碘酶具有利用还原过程降解卤酚的潜力，这种还原过程与大气中的氧气唯一相容。这种酶的一些天然例子已经被研究过，但都是酪氨酸衍生物所特有的。因此，我们的目标是开发新的变种，接受更广泛的底物。将测试三种并行计算方法，以预测产生稳定酶所需的突变，其活性部位几何形状有利于卤酚底物。排名最高的变体将被表达并筛选出所需的活动。进一步的优化将依赖于使用随机突变和基因改组方法的定向进化。这项研究工作应该定义一种通用的方法来调节活性部位的盖子，以适应选定的底物，并提供可测试的产品，用于卤酚去污的工程酶。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.