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造血细胞激酶(HCK)抑制剂发现中的新型虚拟先导物识别:3D QSAR和分子动力学模拟的应用

Novel virtual lead identification in the discovery of hematopoietic cell kinase (HCK) inhibitors: application of 3D QSAR and molecular dynamics simulation.

作者信息

Bavi Rohit, Kumar Raj, Rampogu Shailima, Kim Yongseong, Kwon Yong Jung, Park Seok Ju, Lee Keun Woo

机构信息

a Division of Applied Life Science (BK21 Plus Program) , Systems and Synthetic Agrobiotech Center (SSAC), Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Research Institute of Natural Science (RINS), Gyeongsang National University (GNU) , Jinju , Republic of Korea.

b Department of Science Education , Kyungnam University , Masan , Republic of Korea.

出版信息

J Recept Signal Transduct Res. 2017 Jun;37(3):224-238. doi: 10.1080/10799893.2016.1212376. Epub 2016 Aug 2.

Abstract

High level of hematopoietic cell kinase (Hck) is associated with drug resistance in chronic myeloid leukemia. Additionally, Hck activity has also been connected with the pathogenesis of HIV-1 and chronic obstructive pulmonary disease. In this study, three-dimensional (3D) QSAR pharmacophore models were generated for Hck based on experimentally known inhibitors. A best pharmacophore model, Hypo1, was developed with high correlation coefficient (0.975), Low RMS deviation (0.60) and large cost difference (49.31), containing three ring aromatic and one hydrophobic aliphatic feature. It was further validated by the test set (r = 0.96) and Fisher's randomization method (95%). Hypo 1 was used as a 3D query for screening the chemical databases, and the hits were further screened by applying Lipinski's rule of five and ADMET properties. Selected hit compounds were subjected to molecular docking to identify binding conformations in the active site. Finally, the appropriate binding modes of final hit compounds were revealed by molecular dynamics (MD) simulations and free energy calculation studies. Hence, we propose the final three hit compounds as virtual candidates for Hck inhibitors.

摘要

高水平的造血细胞激酶(Hck)与慢性髓性白血病的耐药性相关。此外,Hck活性还与HIV-1的发病机制和慢性阻塞性肺疾病有关。在本研究中,基于实验已知的抑制剂为Hck生成了三维(3D)QSAR药效团模型。开发了一个最佳药效团模型Hypo1,其具有高相关系数(0.975)、低均方根偏差(0.60)和大成本差异(49.31),包含三个环状芳香族和一个疏水脂肪族特征。通过测试集(r = 0.96)和费舍尔随机化方法(95%)对其进行了进一步验证。Hypo 1用作3D查询以筛选化学数据库,并通过应用Lipinski五规则和ADMET性质对命中结果进行进一步筛选。对选定的命中化合物进行分子对接以确定活性位点中的结合构象。最后,通过分子动力学(MD)模拟和自由能计算研究揭示了最终命中化合物的合适结合模式。因此,我们提出最终的三种命中化合物作为Hck抑制剂的虚拟候选物。

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