Mondal Dibyendu, Kolev Vesselin, Warshel Arieh
Department of Chemistry, University of Southern California, Los Angeles, California 90089, United States.
ACS Catal. 2020 Jun 5;10(11):6002-6012. doi: 10.1021/acscatal.0c01206. Epub 2020 Apr 27.
Computer-aided enzyme design is a field of great potential importance for biotechnological applications, medical advances, and a fundamental understanding of enzyme action. However, reaching a predictive ability in this direction is extremely challenging. It requires both the ability to predict quantitatively the activation barriers in cases where the structure and sequence are known and the ability to predict the effect of different mutations. In this work, we propose a protocol for predicting reasonable starting structures of mutants of proteins with known structures and for calculating the activation barriers of the generated mutants. Our approach also allows us to use the predicted structures of the generated mutant to predict structures and activation barriers for subsequent set of mutations. This protocol is used to examine the reliability of the directed evolution of Kemp eliminase and haloalkane dehalogenase. We also used the results of single and double mutations as a base for predicting the effect of transition-state stabilization by multiple concurrent mutations. This strategy seems to be useful in creating an activity funnel that provides a qualitative ranking of the catalytic power of different mutants.
计算机辅助酶设计对于生物技术应用、医学进步以及对酶作用的基本理解而言,是一个具有极大潜在重要性的领域。然而,在这个方向上实现预测能力极具挑战性。这既需要在已知结构和序列的情况下定量预测活化能垒的能力,也需要预测不同突变效应的能力。在这项工作中,我们提出了一种协议,用于预测具有已知结构的蛋白质突变体的合理起始结构,并计算所生成突变体的活化能垒。我们的方法还使我们能够利用所生成突变体的预测结构来预测后续突变集的结构和活化能垒。该协议用于检验肯普消除酶和卤代烷脱卤酶定向进化的可靠性。我们还将单突变和双突变的结果作为预测多个同时发生的突变对过渡态稳定化作用效果的基础。这种策略似乎有助于创建一个活性漏斗,为不同突变体的催化能力提供定性排名。