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使用比较分子场分析(CoMFA)、比较分子相似性指数分析(CoMSIA)和全息定量构效关系(HQSAR)对禽流感病毒神经氨酸酶抑制剂进行定量构效关系分析。

QSAR analyses on avian influenza virus neuraminidase inhibitors using CoMFA, CoMSIA, and HQSAR.

作者信息

Zheng Mingyue, Yu Kunqian, Liu Hong, Luo Xiaomin, Chen Kaixian, Zhu Weiliang, Jiang Hualiang

机构信息

Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Zhangjiang Hi-Tech Park, Shanghai, 201203, P.R. China.

出版信息

J Comput Aided Mol Des. 2006 Sep;20(9):549-66. doi: 10.1007/s10822-006-9080-0. Epub 2006 Nov 11.

Abstract

The recent wide spreading of the H5N1 avian influenza virus (AIV) in Asia, Europe and Africa and its ability to cause fatal infections in human has raised serious concerns about a pending global flu pandemic. Neuraminidase (NA) inhibitors are currently the only option for treatment or prophylaxis in humans infected with this strain. However, drugs currently on the market often meet with rapidly emerging resistant mutants and only have limited application as inadequate supply of synthetic material. To dig out helpful information for designing potent inhibitors with novel structures against the NA, we used automated docking, CoMFA, CoMSIA, and HQSAR methods to investigate the quantitative structure-activity relationship for 126 NA inhibitors (NIs) with great structural diversities and wide range of bioactivities against influenza A virus. Based on the binding conformations discovered via molecular docking into the crystal structure of NA, CoMFA and CoMSIA models were successfully built with the cross-validated q (2) of 0.813 and 0.771, respectively. HQSAR was also carried out as a complementary study in that HQSAR technique does not require 3D information of these compounds and could provide a detailed molecular fragment contribution to the inhibitory activity. These models also show clearly how steric, electrostatic, hydrophobicity, and individual fragments affect the potency of NA inhibitors. In addition, CoMFA and CoMSIA field distributions are found to be in well agreement with the structural characteristics of the corresponding binding sites. Therefore, the final 3D-QSAR models and the information of the inhibitor-enzyme interaction should be useful in developing novel potent NA inhibitors.

摘要

近期,H5N1禽流感病毒(AIV)在亚洲、欧洲和非洲广泛传播,且能导致人类致命感染,这引发了人们对即将到来的全球流感大流行的严重担忧。神经氨酸酶(NA)抑制剂是目前治疗或预防感染该毒株人类的唯一选择。然而,目前市场上的药物常常遭遇迅速出现的耐药突变体,且由于合成材料供应不足,应用有限。为挖掘有助于设计新型结构强效NA抑制剂的有用信息,我们使用自动对接、比较分子力场分析(CoMFA)、比较分子相似性指数分析(CoMSIA)和高效定量构效关系(HQSAR)方法,研究了126种对甲型流感病毒具有高度结构多样性和广泛生物活性的NA抑制剂(NIs)的定量构效关系。基于通过分子对接进入NA晶体结构所发现的结合构象,成功构建了CoMFA和CoMSIA模型,其交叉验证q(2)分别为0.813和0.771。还开展了HQSAR作为补充研究,因为HQSAR技术不需要这些化合物的三维信息,且能提供对抑制活性的详细分子片段贡献。这些模型还清楚地显示了空间、静电、疏水性和单个片段如何影响NA抑制剂的效力。此外,发现CoMFA和CoMSIA场分布与相应结合位点的结构特征高度一致。因此,最终的三维定量构效关系模型以及抑制剂 - 酶相互作用信息应有助于开发新型强效NA抑制剂。

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