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首页> 外文期刊>RSC Advances >Molecular modeling studies of 1,2,4-triazine derivatives as novel h-DAAO inhibitors by 3D-QSAR, docking and dynamics simulations
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Molecular modeling studies of 1,2,4-triazine derivatives as novel h-DAAO inhibitors by 3D-QSAR, docking and dynamics simulations

机译：用3D-QSAR，对接和动力模拟作为新型H-Daao抑制剂的1,2,4-三嗪衍生物的分子建模研究

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Human d-amino acid oxidase (h-DAAO) can effectively act on d-serine, which has been actively explored as a novel therapeutic target for treating schizophrenia. In this study, 37 h-DAAO inhibitors based on a 6-hydroxy-1,2,4-triazine-3,5(2H,4H)-dione scaffold were obtained to construct the optimal comparative molecular field analysis (CoMFA, q(2) = 0.613, r(2) = 0.966) and comparative molecular similarity index analysis (CoMSIA, q(2) = 0.669, r(2) = 0.985) models. The results indicate that the models have good predictability and strong stability. Furthermore, contour maps of the three-dimensional quantitative structure-activity relationship (3D-QSAR) revealed the relationships between the structural features and inhibitory activity. A total of nine new h-DAAO inhibitors were designed, which exhibited good predicted pIC(50) values. Through molecular docking and molecular dynamics simulation, four essential residues (i.e., Gly313, Arg283, Tyr224 and Tyr228) were considered to interact with the inhibitor. The hydrogen bonds produced by the triazine structure with protein and the hydrophobic interactions with the residues (i.e., Leu51, His217, Gln53 and Leu215) play an important role in the stability of the inhibitor at the binding site of the protein. Additionally, the compounds D1, D3 and D8, with higher predicted activities, were selected by ADME and bioavailability prediction. The present study could offer a reliable theoretical basis for future structural optimisation, design and synthesis of effective antipsychotics.
机译：人D-氨基酸氧化酶（H-DAAO）可以有效地对D-丝氨酸作用，这已被主动探索为治疗精神分裂症的新疗法靶标。在本研究中，获得了基于6-羟基-1,2,4-三嗪-3,5（2H，4H） - 二硫醚支架的37个H-Daao抑制剂，以构建最佳的比较分子场分析（Comfa，Q（ 2）= 0.613，R（2）= 0.966）和对比分子相似性指数分析（COMSIA，Q（2）= 0.669，R（2）= 0.985）模型。结果表明，该模型具有良好的可预测性和强的稳定性。此外，三维定量结构 - 活性关系（3D-QSAR）的轮廓图揭示了结构特征和抑制活动之间的关系。设计了九个新的H-Daao抑制剂，其表现出良好的预测照片（50）值。通过分子对接和分子动力学模拟，认为四个基本残留物（即Gly313，Arg283，Tyr224和Tyr228）与抑制剂相互作用。通过蛋白质和与残基的疏水相互作用产生的氢键（即，Leu51，HIS217，GLN53和Leu215）在蛋白质的结合位点的抑制剂的稳定性中起重要作用。另外，通过ADME和生物利用度预测选择具有更高预测活性的化合物D1，D3和D8。本研究可以为未来的结构优化，设计和合成有效抗精神病药提供可靠的理论依据。

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  • 来源
    《RSC Advances》 |2018年第26期|共17页
  • 作者

    Qian Ping Ping; Wang Shuai; Feng Kai Rui; Ren Yu Jie;

  • 作者单位

    Shanghai Inst Technol Sch Chem &

    Environm Engn Shanghai 201418 Peoples R China;

    Shanghai Inst Technol Sch Chem &

    Environm Engn Shanghai 201418 Peoples R China;

    Shanghai Inst Technol Sch Chem &

    Environm Engn Shanghai 201418 Peoples R China;

    Shanghai Inst Technol Sch Chem &

    Environm Engn Shanghai 201418 Peoples R China;

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