一枝蒿酮酸酰胺衍生物的合成和抗A3, B型流感病毒和 单纯I, II型疱疹病毒活性研究

从新疆一枝蒿中分离得到了单体化合物一枝蒿酮酸, 然后以一枝蒿酮酸和有机胺为原料, 在偶联剂DCC, HOBt/DMAP的作用下, 合成了13种未见文献报道的一枝蒿酮酸酰胺衍生物2a～2m. 所合成的化合物经过IR, 1H NMR, ESI-MS等分析方法进行了表征, 并对化合物2a～2m进行初步的体外抗A3, B型流感病毒和单纯I, II型疱疹病毒活性研究. 初步试验结果表明化合物2a同时具有抗A3, B型流感病毒活性, 而且抗B型流感病毒活性比母体化合物的活性较高. 化合物2d的抗B型流感病毒活性比母体化合物高16倍, 化合物2e同时具有较强的抗单纯I, II型疱疹病毒活性.     

Structural and Thermodynamic Analysis of the Resistance Development to Pimodivir (VX-787), the Clinical Inhibitor of Cap Binding to PB2 Subunit of Influenza A Polymerase

Influenza A virus (IAV) encodes a polymerase composed of three subunits: PA, with endonuclease activity, PB1 with polymerase activity and PB2 with host RNA five-prime cap binding site. Their cooperation and stepwise activation include a process called cap-snatching, which is a crucial step in the IAV life cycle. Reproduction of IAV can be blocked by disrupting the interaction between the PB2 domain and the five-prime cap. An inhibitor of this interaction called pimodivir (VX-787) recently entered the third phase of clinical trial; however, several mutations in PB2 that cause resistance to pimodivir were observed. First major mutation, F404Y, causing resistance was identified during preclinical testing, next the mutation M431I was identified in patients during the second phase of clinical trials. The mutation H357N was identified during testing of IAV strains at Centers for Disease Control and Prevention. We set out to provide a structural and thermodynamic analysis of the interactions between cap-binding domain of PB2 wild-type and PB2 variants bearing these mutations and pimodivir. Here we present four crystal structures of PB2-WT, PB2-F404Y, PB2-M431I and PB2-H357N in complex with pimodivir. We have thermodynamically analysed all PB2 variants and proposed the effect of these mutations on thermodynamic parameters of these interactions and pimodivir resistance development. These data will contribute to understanding the effect of these missense mutations to the resistance development and help to design next generation inhibitors.     

Multivalent Peptide–Nanoparticle Conjugates for Influenza-Virus Inhibition

To inhibit binding of the influenza A virus to the host cell glycocalyx, we generate multivalent peptide–polymer nanoparticles binding with nanomolar affinity to the virus via its spike protein hemagglutinin. The chosen dendritic polyglycerol scaffolds are highly biocompatible and well suited for a multivalent presentation. We could demonstrate in vitro that by increasing the size of the polymer scaffold and adjusting the peptide density, viral infection is drastically reduced. Such a peptide–polymer conjugate qualified also in an in vivo infection scenario. With this study we introduce the first non-carbohydrate-based, covalently linked, multivalent virus inhibitor in the nano- to picomolar range by ensuring low peptide-ligand density on a larger dendritic scaffold.     

Indium-tin-oxide thin film transistor biosensors for label-free detection of avian influenza virus H5N1

As continuous outbreak of avian influenza (AI) has become a threat to human health, economic development and social stability, it is urgently necessary to detect the highly pathogenic avian influenza H5N1 virus quickly. In this study, we fabricated indium-tin-oxide thin-film transistors (ITO TFTs) on a glass substrate for the detecting of AI H5N1. The ITO TFT is fabricated by a one-shadow-mask process in which a channel layer can be simultaneously self-assembled between ITO source/drain electrodes during magnetron sputtering deposition. Monoclonal anti-H5N1 antibodies specific for AI H5N1 virus were covalently immobilized on the ITO channel by (3-glycidoxypropyl)trimethoxysilane. The introduction of target AI H5N1 virus affected the electronic properties of the ITO TFT, which caused a change in the resultant threshold voltage (V_T) and field-effect mobility. The changes of I_D–V_G curves were consistent with an n-type field effect transistor behavior affected by nearby negatively charged AI H5N1 viruses. The transistor based sensor demonstrated high selectivity and stability for AI H5N1 virus sensing. The sensor showed linear response to AI H5N1 in the concentrations range from 5 × 10⁻⁹ g mL⁻¹ to 5 × 10⁻⁶ g mL⁻¹ with a detection limit of 0.8 × 10⁻¹⁰ g mL⁻¹. Moreover, the ITO TFT biosensors can be repeatedly used through the washing processes. With its excellent electric properties and the potential for mass commercial production, ITO TFTs can be promising candidates for the development of label-free biosensors.     

基于机器学习方法的H1N1神经氨酸苷酶抑制剂的分类预测

流感是一种主要的呼吸道传染病, 在普通人群中有着较高的发病率, 而对于一些年老和高危病人还有较高的死亡率. 研究显示抑制神经氨酸苷酶(NA)可以阻断病毒RNA复制, 因此NA是有效治疗H1N1型流感病毒的重要药物靶标. 通过计算机方法进行虚拟筛选和预测NA抑制剂已经变得越来越重要. 针对酶活性位点进行基于结构的合理药物设计, 开发H1N1 病毒神经氨酸苷酶抑制剂, 已成为药物研究的热点之一. 本文通过多种机器学习方法(支持向量机(SVM)、k-最近相邻法(k-NN)和C4.5决策树(C4.5DT))对已知的神经氨酸苷酶抑制剂(NAIs)与非神经氨酸苷酶抑制剂(non-NAIs)建立分类预测模型. 其中227个结构多样性化合物(72个NAIs与155个non-NAIs)被用于测试分类预测系统, 并用递归变量消除法选择与神经氨酸苷酶抑制剂分类相关的性质描述符以提高预测精度. 本研究对独立验证集的总预测精度为75.9%-92.6%, NA 抑制剂的预测精度为64.3%-78.6%, 非H1N1抑制剂的预测精度为77.5%-97.5%. SVM法给出最好的总预测精度(92.6%). 本研究表明支持向量机等机器学习方法可以有效预测未知数据集中潜在的NA抑制剂, 并有助于发现与其相关的分子描述符.     

Identification of potential influenza virus endonuclease inhibitors through virtual screening based on the 3D-QSAR model

Influenza endonucleases have appeared as an attractive target of antiviral therapy for influenza infection. With the purpose of designing a novel antiviral agent with enhanced biological activities against influenza endonuclease, a three-dimensional quantitative structure-activity relationships (3D-QSAR) model was generated based on 34 influenza endonuclease inhibitors. The comparative molecular similarity index analysis (CoMSIA) with a steric, electrostatic and hydrophobic (SEH) model showed the best correlative and predictive capability (q ² = 0.763, r ² = 0.969 and F = 174.785), which provided a pharmacophore composed of the electronegative moiety as well as the bulky hydrophobic group. The CoMSIA model was used as a pharmacophore query in the UNITY search of the ChemDiv compound library to give virtual active compounds. The 3D-QSAR model was then used to predict the activity of the selected compounds, which identified three compounds as the most likely inhibitor candidates.     

流感病毒融合肽磁共振研究进展

流感病毒融合肽在流感病毒感染宿主细胞的过程中扮演关键角色,解析其三维结构是了解病毒融合机制的关键.融合肽结构的研究历经十几年,期间提出了多种融合模型和假说,至今仍然是科学家们感兴趣的热点问题.核磁共振方法是研究融合肽结构的主要手段之一,该文综述了该领域近几年的重要进展,以期对流感病毒融合肽的融合机制有更深入的认识.     

Predicting interspecies transmission of avian influenza virus based on wavelet packet decomposition

Using wavelet packet decomposition, the energy coefficients in the fifth level of viral protein sequences were achieved to predict interspecies transmission. Since avian-origin influenza viruses could have high sequence similarities with human-origin avian influenza virus and could have the phenotype of interspecies transmission, viral data should be filtered to prevent the misconduct of feature selection and false performance of predicting models. Considering the balance of data size, the empirical cut-off value 97% was used to screen avian-origin influenza virus with high sequence similarity. The excellent performances of cross validation show that the SVM model has the best capability of predicting transmission and evaluating the contribution of five amino acid factors. The robust model was finally used to evaluate the filtered data of avian-origin virus and the results confirmed that double check for ambiguous phenotype of avian-origin virus with high sequence similarity was necessary and part of them have the ability to across species barriers.     

Early-warning signals for an outbreak of the influenza pandemic

Over the course of human history, influenza pandemics have been seen as major disasters, so studies on the influenza virus have become an important issue for many experts and scholars. Comprehensive research has been performed over the years on the biological properties, chemical characteristics, external environmental factors and other aspects of the virus, and some results have been achieved. Based on the chaos game representation walk model, this paper uses the time series analysis method to study the DNA sequences of the influenza virus from 1913 to 2010, and works out the early-warning signals indicator value for the outbreak of an influenza pandemic. The variances in the CGR walk sequences for the pandemic years (or + -1 to 2 years) are significantly higher than those for the adjacent years, while those in the non-pandemic years are usually smaller. In this way we can provide an influenza early-warning mechanism so that people can take precautions and be well prepared prior to a pandemic.     

Interdigitated array microelectrode based impedance immunosensor for detection of avian influenza virus H5N1

Continuous outbreaks of avian influenza (AI) in recent years with increasing threat to animals and human health have warranted the urgent need for rapid detection of pathogenic AI viruses. In this study, an impedance immunosensor based on an interdigitated array (IDA) microelectrode was developed as a new application for sensitive, specific and rapid detection of avian influenza virus H5N1. Polyclonal antibodies against AI virus H5N1 surface antigen HA (Hemagglutinin) were oriented on the gold microelectrode surface through protein A. Target H5N1 viruses were then captured by the immobilized antibody, resulting in a change in the impedance of the IDA microelectrode surface. Red blood cells (RBCs) were used as biolabels for further amplification of the binding reaction of the antibody-antigen (virus). The binding of target AI H5N1 onto the antibody-modified IDA microelectrode surface was further confirmed by atomic force microscopy. The impedance immunosensor could detect the target AI H5N1 virus at a titer higher than 10³ EID₅₀/ml (EID₅₀: 50% Egg Infective Dose) within 2 h. The response of the antibody-antigen (virus) interaction was shown to be virus titer-dependent, and a linear range for the titer of H5N1 virus was found between 10³ and 10⁷ EID₅₀/ml. Equivalent circuit analysis indicated that the electron transfer resistance of the redox probe [Fe(CN)₆]^3−/4− and the double layer capacitance were responsible for the impedance change due to the protein A modification, antibody immobilization, BSA (bovine serum albumin) blocking, H5N1 viruses binding and RBCs amplification. No significant interference was observed from non-target RNA viruses such as Newcastle disease virus and Infectious Bronchitis disease virus. (The H5N1 used in the study was inactivated virus.)