Computational design of enzyme–ligand binding using a combined energy function and deterministic sequence optimization algorithm
Computational design of enzyme–ligand binding using a combined energy function and deterministic sequence optimization algorithm
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DOI：
10.1007/s00894-015-2742-x
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发表时间：
2015-07
影响因子：
2.2
通讯作者：
Ye Tian;Xiaoqiang Huang;Yushan Zhu
中科院分区：
文献类型：
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作者：
Ye Tian;Xiaoqiang Huang;Yushan Zhu
配体结合界面处的酶氨基酸序列对于反应是进化优化的，并且酶-配体复合物的天然构象相对于天然样或非天然序列中的替代构象必须具有低自由能。基于这一假设，开发了一个组合的能量函数的酶的设计，然后通过概括天然酶序列在配体结合界面的10个酶-配体复合物进行评估。在这个能量函数中，极性或带电原子之间的静电相互作用在埋界面描述了一个明确的取向依赖性氢键势和一个成对可分解的广义玻恩模型的基础上的一般侧链的蛋白质设计框架。的能量函数增加了一个成对的表面积为基础的非极性原子掩埋的疏水性贡献。使用此功能，平均而言，78%的氨基酸在配体结合位点的预测正确的最小能量序列，而84%的预测正确的最相似的序列，这是从每个酶-配体复合物的前20个序列中选择。在10个复合物中的酶-配体结合界面处的氢键通常以正确的几何形状恢复。使用组合能量函数计算的结合能有助于区分活性序列与通过重复求解一系列混合整数线性规划问题以增加整数切割的序列选择而产生的备选序列的池。
Enzyme amino-acid sequences at ligand-binding interfaces are evolutionarily optimized for reactions, and the natural conformation of an enzyme–ligand complex must have a low free energy relative to alternative conformations in native-like or non-native sequences. Based on this assumption, a combined energy function was developed for enzyme design and then evaluated by recapitulating native enzyme sequences at ligand-binding interfaces for 10 enzyme–ligand complexes. In this energy function, the electrostatic interaction between polar or charged atoms at buried interfaces is described by an explicitly orientation-dependent hydrogen-bonding potential and a pairwise-decomposable generalized Born model based on the general side chain in the protein design framework. The energy function is augmented with a pairwise surface-area based hydrophobic contribution for nonpolar atom burial. Using this function, on average, 78% of the amino acids at ligand-binding sites were predicted correctly in the minimum-energy sequences, whereas 84% were predicted correctly in the most-similar sequences, which were selected from the top 20 sequences for each enzyme–ligand complex. Hydrogen bonds at the enzyme–ligand binding interfaces in the 10 complexes were usually recovered with the correct geometries. The binding energies calculated using the combined energy function helped to discriminate the active sequences from a pool of alternative sequences that were generated by repeatedly solving a series of mixed-integer linear programming problems for sequence selection with increasing integer cuts.