Binding Interaction Analysis of the Active Site and Its Inhibitors for Neuraminidase (N1 Subtype) of Human Influenza Virus by the Integration of Molecular Docking, FMO Calculation and 3D-QSAR CoMFA Mo

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• 作者：Qingye Zhang ; Jiaoyan Yang ; Kun Liang ; Lingling Feng ; Sanpin Li ; Jian Wan ; Xin Xu ; Guangfu Yang ; Deli Liu ; Shao Yang
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2008
• 出版时间：September 22, 2008
• 年：2008
• 卷：48
• 期：9
• 页码：1802-1812
• 全文大小：542K
• 年卷期：v.48,no.9(September 22, 2008)
• ISSN：1549-960X

文摘

Recently, the worldwide spread of A/H5N1 avian influenza with high virulence has highlighted the potential threat of human influenza pandemic. Tamiflu and Relenza are currently the only two anti-influenza drugs targeting the neuraminidase (NA) enzyme of human influenza virus. Reports of the emergence of drug resistance further make the development of new potent anti-influenza inhibitors a priority. The X-ray crystallographic study of A/H5N1 avian influenza NA subtypes () has demonstrated that there exist two genetically distinct groups, group-1 (N1, N4, N5 and N8) and group-2 (N2, N3, N6, N7 and N9), whose conformations are substantially different. The detailed comparison of their active sites has established, heretofore, the most accurate and solid molecular basis of structure and mechanism for the development of new anti-influenza drugs. In the present study, a three-dimensional structure of N1 subtype of human influenza type A virus (N1hA) has been generated by homology modeling using the X-ray crystallographic structure of N1 subtype of avian influenza virus (N1aA) as the template. Binding interaction analysis between the active site and its inhibitors has been performed by combining ab initio fragment molecular orbital (FMO) calculations and three-dimensional quantitative structure−activity relationship with comparative molecular field analysis (3D-QSAR CoMFA) modeling. Integrated with docking-based 3D-QSAR CoMFA modeling, molecular surface property (electrostatic and steric) mapping and FMO pair interaction analysis, a set of new receptor−ligand binding models and bioaffinity predictive models for rational design and virtual screening of more potent inhibitors of N1hA are established. In addition, the flexibility of the loop-150 of N1hA and N1aA has been examined by a series of molecular dynamics simulations.