Substrate-Specific Screening for Mutational Hotspots Using Biased Molecular Dynamics Simulations
Substrate-Specific Screening for Mutational Hotspots Using Biased Molecular Dynamics Simulations
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DOI：
10.1021/acscatal.7b02634
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发表时间：
2017-10-01
期刊：
影响因子：
12.9
通讯作者：
Pelletier, Joelle N.
中科院分区：
文献类型：
--
作者：
Ebert, Maximilian C. C. J. C.;Espinola, Joaquin Guzman;Pelletier, Joelle N.
酶工程中底物特异性突变热点的预测是一项复杂且计算密集型的任务。当可用的晶体结构没有配体，结合所需底物的远同源物，或将配体保持在非生产性构象中时，这变得特别具有挑战性。为了解决这一缺点，我们提出了一种结合分子动力学模拟和分子对接方案来预测催化相关酶配体复合物的构象，即使在没有配体结合结构的情况下。我们应用自适应偏力方法预测了脂肪酸底物从体介质扩散到细胞色素P450 CYP102A1 （BM3）活性位点的配体特异性路径。从一个无配体的晶体结构开始，我们成功地鉴定了所有已知参与棕榈酸与BM3结合的残基。结合轨迹还揭示了一个未知的结合残基Q73，我们通过实验证实了这一点。构建自由能结构表明，与人类细胞色素p450类似，结合是多步骤的，并不遵循简单的Michaelis-Menten动力学。我们使用结构独特的底物，小芳香吲哚，证实了该方法的稳健性。然后，我们将预测的BM3：棕榈酸酯复合物应用于29个棕榈酸酯类似物库的分子对接。这为整个文库产生了催化相关的结合姿势，而直接对接到无配体和配体结合的晶体结构则效果不佳。这种快速而简单的计算方法广泛适用于以特定底物的方式预测结合热点，并且有可能大大减少针对感兴趣底物定制酶的实验筛选工作。
Prediction of substrate-specific mutational hotspots for enzyme engineering is a complex and computationally intensive task. This becomes particularly challenging when the available crystal structures have no ligand, bind a distant homologue of the desired substrate, or hold the ligand in a nonproductive conformation. To address that shortcoming, we present a combined molecular dynamics simulation and molecular docking protocol to predict the conformation of catalytically relevant enzyme ligand complexes even in the absence of a ligand-bound structure. We applied the adaptive biasing force method to predict the ligand-specific path of diffusion of a fatty acid substrate from the bulk media into the active site of cytochrome P450 CYP102A1 (BM3). Starting with a ligand-free crystal structure, we successfully identified all residues known to be involved in palmitic acid binding to BM3. The binding trajectory also revealed a yet unknown binding residue, Q73, which we confirmed experimentally. Building the free-energy landscape illustrates that, similar to human cytochrome P450s, binding is multistep and does not follow simple Michaelis-Menten kinetics. We confirmed the robustness of the method using a structurally distinct substrate, the small aromatic indole. We then applied the predicted BM3:palmitate complex to molecular docking of a library of 29 palmitate analogues. This produced catalytically relevant binding poses for the entire library, while docking directly into ligand-free and ligand-bound crystal structures gave poor results. This fast and simple computational method is broadly applicable for predicting binding hotspots in a substrate-specific manner and has the potential to drastically reduce the experimental screening effort to tailor an enzyme to substrates of interest.