Department of Chemistry, University of Southern California, Los Angeles, CA 90089.
Loschmidt Laboratories, Department of Experimental Biology, Masaryk University, 625 00 Brno, Czech Republic.
Proc Natl Acad Sci U S A. 2019 Jan 8;116(2):389-394. doi: 10.1073/pnas.1804979115. Epub 2018 Dec 26.
Rational enzyme design presents a major challenge that has not been overcome by computational approaches. One of the key challenges is the difficulty in assessing the magnitude of the maximum possible catalytic activity. In an attempt to overcome this challenge, we introduce a strategy that takes an active enzyme (assuming that its activity is close to the maximum possible activity), design mutations that reduce the catalytic activity, and then try to restore that catalysis by mutating other residues. Here we take as a test case the enzyme haloalkane dehalogenase (DhlA), with a 1,2-dichloroethane substrate. We start by demonstrating our ability to reproduce the results of single mutations. Next, we design mutations that reduce the enzyme activity and finally design double mutations that are aimed at restoring the activity. Using the computational predictions as a guide, we conduct an experimental study that confirms our prediction in one case and leads to inconclusive results in another case with 1,2-dichloroethane as substrate. Interestingly, one of our predicted double mutants catalyzes dehalogenation of 1,2-dibromoethane more efficiently than the wild-type enzyme.
理性酶设计提出了一个重大挑战，计算方法尚未克服。其中一个关键挑战是难以评估最大可能催化活性的幅度。为了克服这一挑战，我们引入了一种策略，即采用活性酶（假设其活性接近最大可能活性），设计降低催化活性的突变体，然后尝试通过突变其他残基来恢复催化活性。在这里，我们以酶卤代烷脱卤酶（DhlA）和 1,2-二氯乙烷为底物作为测试案例。我们首先证明我们有能力重现单突变的结果。接下来，我们设计降低酶活性的突变体，最后设计旨在恢复活性的双突变体。使用计算预测作为指导，我们进行了一项实验研究，在一种情况下证实了我们的预测，而在另一种情况下则导致使用 1,2-二氯乙烷作为底物的不确定结果。有趣的是，我们预测的双突变体之一催化 1,2-二溴乙烷脱卤的效率比野生型酶更高。
