禽流感病毒HA蛋白与人受体的分子对接

血凝素(hemagglutinin,HA)是位于禽流感病毒表面的糖蛋白。在病毒感染过程中,HA与禽类宿主细胞表面受体结合,介导病毒膜与宿主核内体膜的融合,在传染过程中发挥关键作用。自然界中的禽流感病毒处于不断演化之中,其HA的禽受体结合位点常常发生氨基酸变异。因此,当HA变异体与人受体结合能力较强时,禽流感病毒往往会发生跨种传播而感染人。为预防禽流感的跨种传播,人们迫切需要发展大规模快速检测或预测HA变异体与人受体结合亲和力的方法,以评估各种新发禽流感病毒的跨种传播能力,提前筛选出有潜在危险的病毒株。针对此问题,本研究以H7N9亚型的HA蛋白H7为研究对象,发展了一种运用分子对接的计算方法,预测HA变异体与人受体的结合亲和力。该方法的计算结果表明,H7与人受体的结合亲和力普遍弱于有较强传染人能力的H1,说明H7N9亚型病毒的跨种传播能力普遍较弱;但是,计算分析也揭示,部分新发的H7N9毒株的HA有强的人受体结合亲和力,提示在自然演化过程中,H7N9病毒有可能演化出具有较强的感染人能力的新毒株,这与2013年禽流感疫情的实际发生情况相一致。因此,本文所发展的计算方法可用于快速预测新发禽流感病毒HA与人受体的结合亲和力,为新发禽流感病毒的跨种传播风险评估提供理论依据。     

Detection of influenza A virus using carbon nanotubes field effect transistor based DNA sensor

The carbon nanotubes field effect transistor (CNTFET) based DNA sensor was developed, in this paper, for detection of influenza A virus DNA. Number of factors that influence the output signal and analytical results were investigated. The initial probe DNA, decides the available DNA strands on CNTs, was 10 µM. The hybridization time for defined single helix was 120 min. The hybridization temperature was set at 30 °C to get a net change in drain current of the DNA sensor without altering properties of any biological compounds. The response time of the DNA sensor was less than one minute with a high reproducibility. In addition, the DNA sensor has a wide linear detection range from 1 pM to 10 nM, and a very low detection limit of 1 pM. Finally, after 7-month storage in 7.4 pH buffer, the output signal of DNA sensor recovered 97%.     

Enantioselective syntheses of (−)-pinellic acid, α- and β-dimorphecolic acid

An efficient enantioselective convergent approach for the synthesis of (−)-pinellic acid 1, α- and β-dimorphecolic acid (2 and 3) from 1,9-nonane diol is described. The synthetic strategy features Sharpless asymmetric hydroxylation, Sonogashira coupling and Birch reduction.     

Label-free, arrayed sensing of immune response to influenza antigens

Periodic outbreaks of pandemic influenza have been a devastating cause of human mortality over the past century. More recently, an avian influenza strain, designated H5N1, has been identified as having the potential to cause a zoogenic pandemic in humans, and a current outbreak of a new H1N1 influenza variant hypothesized to be of swine origin is of considerable concern. In order to facilitate surveillance and the rapid assessment and comparison of vaccination efforts, a high-throughput assay is highly desirable to supplement standard methods, which require high biosafety-level facilities. In this paper, we describe the design, production, and preliminary evaluation of an antigen array incorporating a panel of hemagglutinins as a platform for the detection and rapid quantification of influenza-specific antibodies in human serum by Arrayed Imaging Reflectometry (AIR), a label-free optical biosensor.     

Detection of influenza A virus based on fluorescence resonance energy transfer from quantum dots to carbon nanotubes

In this paper, a simple and sensitive approach for H5N1 DNA detection was described based on the fluorescence resonance energy transfer (FRET) from quantum dots (QDs) to carbon nanotubes (CNTs) in a QDs-ssDNA/oxCNTs system, in which the QDs (CdTe) modified with ssDNA were used as donors. In the initial stage, with the strong interaction between ssDNA and oxCNTs, QDs fluorescence was effectively quenched. Upon the recognition of the target, the effective competitive bindings of it to QDs-ssDNA occurred, which decreased the interactions between the QDs-ssDNA and oxCNTs, leading to the recovery of the QDs fluorescence. The recovered fluorescence of QDs was linearly proportional to the concentration of the target in the range of 0.01–20 μM with a detection limit of 9.39 nM. Moreover, even a single-base mismatched target with the same concentration of target DNA can only recover a limited low fluorescence of QDs, illustrating the good anti-interference performance of this QDs-ssDNA/oxCNTs system. This FRET platform in the QDs-ssDNA/oxCNTs system was facilitated to the simple, sensitive and quantitative detection of virus nucleic acids and could have a wide range of applications in molecular diagnosis.     

Pharmacophore Mode lingand Virtual Screening to Design the Potential Influenza Virus Endonuclease Inhibitors

Influenza virus endonuclease is an attractive target for antiviral therapy in the treatment of influenza infection. The purpos e of this study is to design a novel antiviral agent with improved biological activities against the influenza virus endonuclease. In this study, chemical feature‐based 3D pharmacophore models were developed from 41 known influenza virus endonuclease inhibitors. The best quantitative pharmacohore model (Hypo 1), which consists of two hydrogen‐bond acceptors and two hydrophobic features, yields the highest correlation coefficient (R = 0.886). Hypo 1 was further validated by the cross validation method and the test set compounds. The application of this model for predicting the activities of 11 known influenza virus endonuclease inhibitors in the test set shows great success. The correlation coefficient of 0.942 and a cross validation of 95;% confidence level prove that this model is reliable in identifying structurally diverse compounds for influenza virus endonuclease inhibition. The most active compound (compound 1) from the training set was docked into the active site of the influenza virus endonuclease as an additional verification that the pharmacophore model is accurate. The docked conformation showed important hydrogen bond interactions between the compound and two amino acids, Lys 134 and Lys 137. After validation, this model was used to screen the NCI chemical database to identify new influenza virus endonuclease inhibitors. Our study shows that the to pranking compound out of the 10 newly identified compounds using fit value ranking has an estimated activity of 0.049 μM. These newly identified lead compounds can be further experimentally validated using in vitro techniques.     

Reservation and allocation policies for influenza vaccines

This research investigates the impact of alternative allocation mechanisms that can be employed in the context of vaccine inventory rationing. Available vaccine inventory can be allocated to arrivals from high priority (target groups such as healthcare professionals) and low priority (non-target groups) demand classes using Partitioned Allocation (PA), Standard Nesting (SN), and Theft Nesting (TN). In any one of the mechanisms, a part of the available inventory is reserved for the exclusive use of the high priority demand class. They differ, however, in how the unreserved portion of the inventory is utilized: Under PA, demand from the high (low) priority class consumes only the reserved (unreserved) quantity. Under SN, demand from the high priority class first consumes the reserved quantity; once and if this quantity is exhausted, high priority demand competes with low priority demand for the remaining inventory. Under TN the sequence of allocation is reversed: both demand classes first compete for the unreserved inventory. Once this portion of inventory is exhausted, high priority demand is fulfilled from the reserved inventory and low priority demand is rejected. We develop service level (probability of fulfilling the entire demand) and fill rate (fraction of demand fulfilled) expressions for all three allocation mechanisms. Based on these expressions, numerical analyses are conducted to illustrate which allocation mechanism a health planner should choose depending on the availability of vaccines, and how the health planner should set the reserved quantity for the high priority class. We observe that (1) there exist certain conditions under which one of the allocation mechanisms outperforms the others and (2) this effect is determined by the decision maker’s choice of the performance measure.