In silico panning for a non-competitive peptide inhibitor.
In silico panning for a non-competitive peptide inhibitor.
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DOI：
10.1186/1471-2105-8-11
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发表时间：
2007-01-12
影响因子：
3
通讯作者：
Sode, Koji
中科院分区：
文献类型：
--
作者：
Yagi, Yukiko;Terada, Kotaro;Noma, Takahisa;Ikebukuro, Kazunori;Sode, Koji
肽配体作为有效药物具有巨大的治疗潜力。目前，市场上有超过 40 种肽可用于药物。然而，由于昂贵且耗时的合成程序对高通量筛选来说是一个问题，因此需要新的程序来减少筛选肽配体所涉及的时间和劳动力。我们提出了“计算机淘选”的新方法，该方法包括两阶段筛选，包括通过对接模拟进行亲和力选择以及使用遗传算法（GA）进行肽配体的进化。计算机淘选成功应用于水溶性醌蛋白葡萄糖脱氢酶（PQQGDH）肽抑制剂的选择。目标酶的肽配体的进化是通过将对接模拟与使用遗传算法（GA）的肽配体进化相结合来实现的，该算法模仿达尔文进化论。在对接模拟中将目标区域指定为紧邻酶的底物结合位点，从而能够选择非竞争性抑制剂。总共进行了四轮计算机选拔；每代对接能量的分布逐渐减少，并且在四轮选择中观察到对接能量的改善。 “SERG”是对接能量最低的前三种肽之一，显示出抑制作用，Ki 值为 20 μM。在该肽存在的情况下，就 Vmax 值而言，PQQGDH 活性比野生型酶低 3 倍。 SERG 阻断酶的机制被确定为非竞争性抑制。我们证实了肽的特异性结合，通过表面等离子共振（SPR）分析计算出其平衡解离常数（KD）值为60 μM。我们展示了一种有效的计算机淘选方法，用于从小型虚拟肽库中选择非竞争性肽抑制剂。这项研究首次使用实验数据证明了计算机进化的有用性。我们的研究强调了这种策略对于基于结构的酶抑制剂筛选的有用性。
Peptide ligands have tremendous therapeutic potential as efficacious drugs. Currently, more than 40 peptides are available in the market for a drug. However, since costly and time-consuming synthesis procedures represent a problem for high-throughput screening, novel procedures to reduce the time and labor involved in screening peptide ligands are required. We propose the novel approach of 'in silico panning' which consists of a two-stage screening, involving affinity selection by docking simulation and evolution of the peptide ligand using genetic algorithms (GAs). In silico panning was successfully applied to the selection of peptide inhibitor for water-soluble quinoprotein glucose dehydrogenase (PQQGDH). The evolution of peptide ligands for a target enzyme was achieved by combining a docking simulation with evolution of the peptide ligand using genetic algorithms (GAs), which mimic Darwinian evolution. Designation of the target area as next to the substrate-binding site of the enzyme in the docking simulation enabled the selection of a non-competitive inhibitor. In all, four rounds of selection were carried out on the computer; the distribution of the docking energy decreased gradually for each generation and improvements in the docking energy were observed over the four rounds of selection. One of the top three selected peptides with the lowest docking energy, 'SERG' showed an inhibitory effect with Ki value of 20 μM. PQQGDH activity, in terms of the Vmax value, was 3-fold lower than that of the wild-type enzyme in the presence of this peptide. The mechanism of the SERG blockage of the enzyme was identified as non-competitive inhibition. We confirmed the specific binding of the peptide, and its equilibrium dissociation constant (KD) value was calculated as 60 μM by surface plasmon resonance (SPR) analysis. We demonstrate an effective methodology of in silico panning for the selection of a non-competitive peptide inhibitor from small virtual peptide library. This study is the first to demonstrate the usefulness of in silico evolution using experimental data. Our study highlights the usefulness of this strategy for structure-based screening of enzyme inhibitors.
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影响因子：
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作者：
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作者：
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Sode, Koji
影响因子：
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DOI：
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发表时间：
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影响因子：
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作者：
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通讯作者：
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