Systematic optimization model and algorithm for binding sequence selection in computational enzyme design
Systematic optimization model and algorithm for binding sequence selection in computational enzyme design
复制标题
计算酶设计中结合序列选择的系统优化模型和算法
DOI：
10.1002/pro.2275
复制
发表时间：
2013-07-01
期刊：
影响因子：
8
通讯作者：
Zhu, Yushan
中科院分区：
文献类型：
--
作者：
Huang, Xiaoqiang;Han, Kehang;Zhu, Yushan
基于酶催化过渡态理论和图论建模，建立了计算酶设计中结合序列选择的系统优化模型。反应体系自由能面上的鞍点用催化几何约束来表示，通过最小化活性中心与过渡态之间的结合能来降低反应的活化能垒。在蛋白质核心序列选择问题的启发下，利用一种新的启发式全局优化算法解决了超大规模组合优化问题。对两个酶催化的水解反应进行了天然活性中心的序列重现实验，以评估设计方法的预测能力。计算结果表明，如果考虑催化剂的几何约束和底物的结构基序，大多数天然结合部位都能被成功识别。可靠地预测活性中心序列可能对创造能够催化靶向化学反应的新型酶具有重要意义。
A systematic optimization model for binding sequence selection in computational enzyme design was developed based on the transition state theory of enzyme catalysis and graph-theoretical modeling. The saddle point on the free energy surface of the reaction system was represented by catalytic geometrical constraints, and the binding energy between the active site and transition state was minimized to reduce the activation energy barrier. The resulting hyperscale combinatorial optimization problem was tackled using a novel heuristic global optimization algorithm, which was inspired and tested by the protein core sequence selection problem. The sequence recapitulation tests on native active sites for two enzyme catalyzed hydrolytic reactions were applied to evaluate the predictive power of the design methodology. The results of the calculation show that most of the native binding sites can be successfully identified if the catalytic geometrical constraints and the structural motifs of the substrate are taken into account. Reliably predicting active site sequences may have significant implications for the creation of novel enzymes that are capable of catalyzing targeted chemical reactions.