HIV-1逆转录酶的分子对接及运动功能相关性分析

目的研究逆转录酶的运动性和生理功能的关系,以及N-乙酰基-β-芳基-1,2-二脱氢乙胺类衍生化合物与其的分子识别,方法采用高斯网络模型和各向异性网络模型研究了p66和p66-DNA的运动模式差异,并用分子对接方法研究化合物与逆转录酶的识别.结果 DNA的结合对p66各区域的运动方向影响不大,但其运动的幅度大大降低.分子对接结果发现Y115和M184的疏水结构在识别的过程中起到重要作用.结论基于各个区域的运动方向分析,推测手指区和RNase H区的开合运动可能是逆转录酶发挥逆转录功能的重要原因.并且,N-乙酰基-β-芳基-1,2-二脱氢乙胺类衍生化合物的N-甲基取代和反式的双键结构更有利于与逆转录酶的识别     

葡糖衍生手性N-杂环卡宾前体波谱学数据分析

以溴代正丁烷与1-（2,3,4,6-四-O-乙酰基-β-D-吡喃葡萄糖基）咪唑（化合物1）为原料合成了溴化1-（2,3,4,6-四-O-乙酰基-β-D-吡喃葡萄糖基）-3-正丁基咪唑盐（化合物2）,它是葡萄糖衍生的手性N-杂环卡宾前体.化合物2的结构中存在多个手性碳原子,导致它的核磁共振（NMR）谱较为复杂.在此,用元素分析、红外吸收光谱（IR）以及液相色谱-高分辨质谱（LC-HRMS）对它的组成进行了分析,然后利用1D和2D NMR谱（包括¹H NMR、¹³C NMR、DEPT135、DEPT90、DEPT45、COSY、¹H-¹³C HSQC、¹H-¹³C HMBC）对化合物2的¹H和¹³C NMR信号进行了归属.     

β-环糊精与1,2-苯并蒽络合的荧光研究

通过测量荧光寿命和荧光光谱,研究了1,2-苯并蒽(BA),9,10-二甲基-1,2-苯并蒽(DMBA)与β-环糊精(β-CD)络合过程及荧光猝灭。计算出络合平衡常数和猝灭常数。结果表明,BA与β-CD发生了络合作用,DMBA几乎不与β-CD络合。加入β-CD可使荧光分子的,聚集态与单体间的平衡向生成单体的方向移动,碘离子对BA的猝灭作用也明显减弱。     

具有不同取代基团的香豆素系列分子二阶非线性光学性质的DFT研究

本文设计了具有不同取代基团的7-苯乙烯基香豆素和4-苯乙烯基香豆素的A、B两个系列共14个化合物分子.采用密度泛函理论B3LYP/6-31G方法对其几何构型进行了全结构优化.在所得优化结构的基础上对这些分子的稳态二阶非线性光学(NLO)系数β值进行计算分析,同时用含时密度泛函理论(TD-DFT)对这些分子的电子性质进行了研究.结果表明:此类香豆素化合物具有较大的分子β值,其中A类分子的共面性好,共轭链长,β值均比B类分子的大.14个化合物中前线分子轨道能级差越小的化合物,其βwt值越大.各分子前线分子轨道跃迁对二阶NLO效应有明显的贡献.     

NNAL模拟模板分子印迹聚合物的合成与固相萃取性能

以三种4-甲基亚硝胺-1-(3-吡啶基)-1-丁醇(NNAL)的结构类似物即4-(N-甲基-N-乙酰基)-1-(3-吡啶基)-1-丁醇、4-(N-甲基)-1-(3-吡啶基)-1-丁醇、1-(3-吡啶基)-1,4-丁二醇为模拟模板分子,甲基丙烯酸(MAA)为功能单体,通过自组装技术制备了对NNAL具有良好识别能力的印迹聚合物．通过X射线光电子能谱和红外光谱研究了NNAL和MAA之间的相互作用,结果表明NNAL和MAA可以通过氢键协同作用形成1:2型配合物．吡啶上的N和亚硝基中的O是形成氢键作用的两个选择性识别位点．XPS和IR进一步揭示出由4-(N-甲基-N-乙酰基)-1-(3-吡啶基)-1-丁醇制备得到的印迹聚合物对NNAL有最佳的识别性能．此外,实验研究了该聚合物作为固相萃取填料分离、净化NNAL的最佳条件．当采用水溶液上样,分别以0.5 mL水、1 mL甲苯、1 mL甲苯/二氯甲烷(9:1)、1 mL甲苯/二氯甲烷(4:1)淋洗,3￡1 mL甲醇洗脱时,NNAL在分子印迹固相萃取柱上的回收率达到93%．以尼古丁为竞争分子的选择性实验进一步证明该材料有很好的特异性识别能力．同时在不同加标水平尿液(500 pg/mL,1000 pg/mL,2000 pg/mL)的回收实验中,NNAL的回收率范围为87.2%～101.2%,精密度值均低于7.1%．     

具有不同取代基团的香豆素系列分子二阶非线性光学性质的DFT研究

本文设计了具有不同取代基团的7-苯乙烯基香豆素和4-苯乙烯基香豆素的A、B两个系列共14个化合物分子。采用密度泛函理论B3LYP/6-31G方法对其几何构型进行了全结构优化．在所得优化结构的基础上对这些分子的稳态二阶非线性光学（NLO）系数β值进行计算分析,同时用含时密度泛函理论（TD-DFT）对这些分子的电子性质进行了研究．结果表明：此类香豆素化合物具有较大的分子β值,其中A类分子的共面性好,共轭链长,β值均比B类分子的大．14个化合物中前线分子轨道能级差越小的化合物,其βtot值越大．各分子前线分子轨道跃迁对二阶NLO效应有明显的贡献．     

四种4-N,N-二苯胺基均二苯乙烯类电致发光材料电子结构和光谱性质的理论计算

用从头算HF和密度泛函B3LYP方法对4种4-N,N-二苯胺基均二苯乙烯类化合物4-N,N-二苯胺基均二苯乙烯(a)、2-氯-4'-N,N-二苯胺基均二苯乙烯(b)、2,6-二氯-4'-N,N-二苯胺基均二苯乙烯(c)及2,6-二甲氧基-4'-N,N-二苯胺基均二苯乙烯(d)进行全优化,并用CIS优化a及d分子的激发态结构.用TDDFT方法计算吸收和发射光谱,考查了溶剂对吸收光谱的影响.结果表明,该类化合物在基态与激发态的跃迁,主要是电子云分布从离域到定域的转变.吸收及发射光谱的计算结果与实验值一致,溶剂对四种化合物的吸收光谱影响不大,而对化合物b及c的强度影响较大.     

2,4,6-三甲氧基苯-1-O-D葡萄糖苷的核磁共振谱的理论研究

应用规范不变原子轨道GIAO法,分别在HF/6-311+G(2d,p)//B3LYP/6-31G(d)和HF/6-311+G(2d,p)//B3LYP/6-31G(d,p)水平上,计算了从卫茅科南蛇藤属植物苦皮藤中分离鉴定出的2,4,6-三甲氧基苯-1-O-D葡萄糖苷(化合物1)的α和β分子构型的1HNMR和13CNMR的化学位移值,并对理论计算值与实验值的误差进行了统计分析,其中β分子构型的计算值与实验值较为接近,结合α和β分子构型的总能量计算值,预测化合物1分子应择型于β构型,即为2,4,6-三甲氧基苯-1-O-β-D葡萄糖苷,这与根据糖的端基质子化学位移和耦合常数实验值(δH=4.81,J=7.3Hz)推断的结论相吻合,进一步说明理论计算的合理性.     

衍生化气相色谱质谱联用法同时测定烟叶多种植物甾醇

以丙酮为提取剂、1％硫酸-乙醇(V∶V)溶液和2.0 mol/L氢氧化钾-乙醇分别作水解剂和皂化剂,利用三甲基氯硅烷和六甲基二硅烷作为硅醚化衍生试剂,采用气相色谱质谱联用仪同时检测烤烟烟叶中的多种甾醇化合物.采用内标校准曲线法对胆甾醇、菜油甾醇、豆甾醇、β-谷甾醇进行准确定量分析;利用内标相对定量法对p香树脂醇、豆甾-...     

光电功能材料

TB342007010823有机光致变色材料的合成与多阶存储实验研究=Synthe-sis of novel organic photochromic diaylethene and multi-level recording experi mental performance[刊,中]/刘学东(清华大学化学系有机光电子分子与分子工程重点实验室.北京(100084)),石明…//功能材料与器件学报.—2006,12(2).—117-119介绍了用于多阶光存储材料的有机光致变色的二芳基乙烯化合物合成,存储的膜片制作和多阶光存储实验。结果显示:用1,2-双(2-甲基-5-(4-醛基苯基)噻吩-3-基)全氟环戊烯作为多阶光存储的记录材料,与PMMA掺杂,采用旋涂法制成存储膜片,…     

A lower bound for the memory capacity in the Potts-Hopfield model

We consider Potts-Hopfield networks of sizeN. We prove the result: _c >0 such that for all 0<< _c we can find, >0 in such a way that, whenN, we can store N patterns, all of them being sorrounded by -energy barriers at distance.     

Analyzing the causation of a railway accident based on a complex network

In this paper, a new model is constructed for the causation analysis of railway accident based on the complex network theory. In the model, the nodes are defined as various manifest or latent accident causal factors. By employing the complex network theory, especially its statistical indicators, the railway accident as well as its key causations can be analyzed from the overall perspective. As a case, the ＂7.23＂ China-Yongwen railway accident is illustrated based on this model. The results show that the inspection of signals and the checking of line conditions before trains run played an important role in this railway accident. In conclusion, the constructed model gives a theoretical clue for railway accident prediction and, hence, greatly reduces the occurrence of railway accidents.     

The uniaxial brickwork model,exact results,and CVM approximation

A complete phase diagram of the uniaxial brickwork lattice is determined first by using exact results, and then by using the cluster variation method. Both results are in very good agreement, which demonstrates the reliability of the CVM for two-dimensional systems. A well-defined maximum in the exact specific heat and a divergence of the CVM susceptibility provide strong indication for the occurrence of a floating phase.     

Space evolution model and empirical analysis of an urban public transport network

This study explores the space evolution of an urban public transport network, using empirical evidence and a simulation model validated on that data. Public transport patterns primarily depend on traffic spatial-distribution, demands of passengers and expected utility of investors. Evolution is an iterative process of satisfying the needs of passengers and investors based on a given traffic spatial-distribution. The temporal change of urban public transport network is evaluated both using topological measures and spatial ones. The simulation model is validated using empirical data from nine big cities in China. Statistical analyses on topological and spatial attributes suggest that an evolution network with traffic demands characterized by power-law numerical values which distribute in a mode of concentric circles tallies well with these nine cities.     

A model for the spread of rumors in Barrat–Barthelemy–Vespignani (BBV) networks

Rumor propagation is a typical form of social communication and plays a significant role in social life. In this paper, we studied the process of rumor propagation by accounting for the mechanism of forgetting in Barrat–Barthelemy–Vespignani (BBV) networks. First, we derived mean-field equations for rumor propagation based on the strength of the nodes in the propagation network. We then analyzed the stability of the model to determine whether a propagation threshold existed in the BBV networks. We also conducted numerical simulations of the BBV networks and found that rumors propagate more slowly in BBV networks than in unweighted networks. The numerical simulation results also demonstrated that as the forgetting rate increases, the rumor’s influence decreases in both BBV networks and unweighted networks. Finally, the simulation results confirmed that a threshold exists for rumor propagation in BBV networks, but that it was independent of the value of the stifling rate.     

Advances in theoretical models of network science

In this review article, we will summarize the main advances in network science investigated by the CIAE Group of Complex Network in this field. Several theoretical models of network science were proposed and their topological and dynamical properties are reviewed and compared with the other models. Our models mainly include a harmonious unifying hybrid preferential model, a large unifying hybrid network model, a quantum interference network, a hexagonal nanowire network, and a small-world network with the same degree. The models above reveal some new phenomena and findings, which are useful for deeply understanding and investigating complex networks and their applications.      

The classification and analysis of dynamic networks

In this paper we, firstly, classify the complex networks in which the nodes are of the lifetime distribution. Secondly, in order to study complex networks in terms of queuing system and homogeneous Markov chain, we establish the relation between the complex networks and queuing system, providing a new way of studying complex networks. Thirdly, we prove that there exist stationary degree distributions of M--G--P network, and obtain the analytic expression of the distribution by means of Markov chain theory. We also obtain the average path length and clustering coefficient of the network. The results show that M--G--P network is not only scale-free but also of a small-world feature in proper conditions.     

Influenza epidemic spread simulation for Poland — a large scale, individual based model study

In this work a construction of an agent based model for studying the effects of influenza epidemic in large scale (38 million individuals) stochastic simulations, together with the resulting various scenarios of disease spread in Poland are reported. Simple transportation rules were employed to mimic individuals’ travels in dynamic route-changing schemes, allowing for the infection spread during a journey. Parameter space was checked for stable behaviour, especially towards the effective infection transmission rate variability. Although the model reported here is based on quite simple assumptions, it allowed to observe two different types of epidemic scenarios: characteristic for urban and rural areas. This differentiates it from the results obtained in the analogous studies for the UK or US, where settlement and daily commuting patterns are both substantially different and more diverse. The resulting epidemic scenarios from these ABM simulations were compared with simple, differential equations based, SIR models — both types of the results displaying strong similarities. The pDYN software platform developed here is currently used in the next stage of the project employed to study various epidemic mitigation strategies.     

节点数加速增长的复杂网络生长模型

受某些实际网络节点数按几何级数增长现象的启发，构造了每个时间步中按当前网络规模成比例地同时加入多个节点的节点数加速增长的网络模型.研究表明，在增长率不是很大的情况下网络度分布仍然是幂律的，但在不同的增长率r下幂律指数是不同的.得到了幂律指数介于2到3之间可调的无标度网络模型，并解析地给出了幂律指数随增长率变化的函数关系.数值模拟还显示，网络的平均最短距离随r减小而簇系数随r增大. 关键词： 复杂网络 无标度网络 生长网络模型 节点数加速增长网络模型     

Deterministic self-similar models of complex networks based on very symmetric graphs

Using very symmetric graphs we generalize several deterministic self-similar models of complex networks and we calculate the main network parameters of our generalization. More specifically, we calculate the order, size and the degree distribution, and we give an upper bound for the diameter and a lower bound for the clustering coefficient. These results yield conditions under which the network is a self-similar and scale-free small world network. We remark that all these conditions are posed on a small base graph which is used in the construction. As a consequence, we can construct complex networks having prescribed properties. We demonstrate this fact on the clustering coefficient. We propose eight new infinite classes of complex networks. One of these new classes is so rich that it is parametrized by three independent parameters.