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Research On The Drug Molecular Dynamics And Metabolism Core Of Recombinated H9N2AIV Strain

Posted on:2013-02-05Degree:DoctorType:Dissertation
Country:ChinaCandidate:X D LiuFull Text:PDF
GTID:1114330371996728Subject:Computational Mechanics
Abstract/Summary:PDF Full Text Request
H9N2avian influenza virus has raged in poultry since its detection in1966, causing high mortality around the world, especially after the pigs and human were detected to be infected and then dead in recent years. The World Health Organization (WHO) had warned that H9N2avian influenza may cause another pandemic flu, indicating the significant potential damage for human's health from H9N2. Consequently, it is essential to enhance the supervision for and research and analysis of the epidemic situation. In the heterologous protein of H9N2avian influenza virus, there are hemagglutinin sequences (HA), neuraminidase sequences (NA) and matrix protein (M2) etc. which play a key role in the infection, reproduction, and mutation of the virus. In the meantime, the infection of and resistance against H9N2virus are closely related to human metabolic system. As a result, the research on HA, NA, M2and the metabolic system is of vital importance to prevent human infection of H9N2virus. This is the objective of this study.At present, studies on H9N2virus are from the perspectives of heredity, variability, drug-resistance as well as the interactions to human physiology system. In this dissertation, the approaches of sequence alignment algorithm, recombination analysis, homology modeling, structure optimization, and molecular docking were employed to study the variability and drug-resistance of HA, NA, M2protein in H9N2avian influenza virus. The simulated annealing and complex network algorithms were applied to extract the core module of human metabolism and find out the metabolites and metabolic reaction parts that are the most closely related to disease infections and drug effects. Directed towards H9N2virus and main human metabolic system, a series of basic researches were carried out through the approaches of arithmetic disposal, optimization calculation and mechanical analysis and so on.There are three parts in this dissertation, and the research work mainly covers the following aspects:The codon usage bias and recombination have been analyzed on HA genes and NA genes in H9N2subtype AIV isolated in China. The results show that the codon usage bias of HA genes and NA genes in H9N2virus is not very evident, which is quite different from the fact that H9N2AIV belongs to GC-deficiency genome. In addition, the mutation bias in HA genes and NA genes is not decisive factors to determine the codon usage mode. The research has found that HA and NA gene recombination does exist. Two cases of recombination of HA genes and NA genes in H9N2AIV isolated in China have been identified respectively in the gene order samples, indirectly proving that the HA and NA genes have the highest variation frequency in the viruses. Based on the above results and the facts that the parasitifer has been spread to mammals and human beings from avian species, it concludes that the H9N2AIV would mutate and recombine more frequently and that its infectivity and virulence would increase greatly. It is more likely that H9N2may become the prototype virus strain of epidemic influenza, which has been cautioned by WHO.Analysis has been performed to drug resistance and drug target sites of M2protein which is attributed to the heterologous protein in H9N2AIV with HA and NA. Epidemic prevention has been taken against H9N2virus which poses a threat to human beings, and drug design has been made in advance. Approaches of homology modeling were applied in constructing the three-dimensional models for M2protein for H9N2avian influenza viruses. Molecular docking was further employed to investigate the mechanism of actions of frequently-used influenza inhibitor (amantadine and rimantadine hydrochloride) to the M2protein. Then, by employing the molecular dynamics method, structural optimization study has been done on M2protein and drug complexes, and the most interactional residues and the most interactional residues and atoms have been identified. It is noted that, among two most conserved binding site and one most active binding sites, all the M2protein residues which are coordinated with influenza inhibitors lie in the second most active binding site. Afterwards, the correctness of the molecular docking is re-examined. In the end, all the theoretically important binding sites are mapped onto the M2protein structure, pointing out the locations of several potential drug targets. The above research results demonstrate that the binding sites of the most conserved residues can be identified as the potential targets of general anti-influenza drugs; the second most active binding sites are the targets of common drugs--amantadine and rimantadine hydrochloride; the other two binding sites are also the underlying new drug targets. Meanwhile, it has been proved that amantadine and rimantadine hydrochloride have good control effect against recent outbreak of Fujian strain H9N2epidemic in China.In order to cope with the threat of influenza pandemic to people caused by H9N2virus, and to learn about the metabolic reactions and metabolites which play a key role in human metabolic system for virus infection and drug therapy. In this dissertation, the core module in human metabolic system is given further analysis, through employing the algorithms of simulated annealing and complex network. According to the bow tie structure of the metabolic network, the preliminary module partition is made of the metabolic network of human and halophilic archaea and the core part in the network system--giant strong component--is extracted. The general structural properties of "small-world effect","scale-free properties" and "self-similarity properties" and so on are tested and verified. Moreover, their biological and pharmacological significances are discussed from the angles of network community structure and centrality analysis.
Keywords/Search Tags:Calculation Biomechanics, Molecular Dynamics, Complex Network, Homology Modeling, Molecular Docking, Metabolism Network
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