环糊精与咖啡豆α-半乳糖苷酶的分子对接研究

通过分子对接方法研究3种主要的环糊精(α-环糊精、β-环糊精及γ-环糊精)与咖啡豆α-半乳糖苷酶的相互作用模型与分子机理。结果表明,咖啡豆α-半乳糖苷酶活性口袋中的关键氨基酸残基为:Trp31、Trp179、Asp200,环糊精中的关键基团为:次甲基上的羟基、亚甲基上的羟基。环糊精覆盖在咖啡豆α-半乳糖苷酶亲水活性空腔的表面,从而抑制其活性,β-环糊精的抑制作用较为明显。分子对接结果为酶法合成α-半乳糖基-环糊精的相互作用研究提供了理论依据。     

用分子对接方法研究肝素与孕激素受体相互结合模式(英文)

用分子对接模拟软件研究了肝素与孕激素受体的相互作用。以肝素中的一糖单位作为探针对孕激素受体蛋白进行搜索,获得肝素组成单位与孕激素受体的特异性结合模式。结果发现,2-O-硫酸-α-L 艾杜糖醛酸(2-O-sulfated iduronic acid,IdoA(2S))作为肝素的核心组成单糖之一,与孕激素受体的结合能力最好。分子对接结果显示 IdoA(2S)深入到孕激素受体的 helix2 和 helix 11 所包围的结合口袋,与孕激素受体结合结构域关键残基 Asn 719 形成稳固的氢键;并与孕激素受体结合结构域的关键残基 Met 909 残基侧链近距离接触,揭示了 IdoA(2S)可能具有的孕激素受体拮抗效应的分子作用机制。本模拟实验所建立的模型能够部分解释肝素抑制孕激素依赖性乳腺癌的现象,同时推测了其相应机理。     

黑沙蒿中4种黄酮类化合物抗氧化活性的DFT研究

采用量子化学密度泛函理论(DFT)的B3LYP/6-311G(d,p)//B3LYP/6-31G(d,p)方法对黑沙蒿中已分离得到的4种黄酮类化合物芹菜素-7,4’二甲醚、芜花素、羟基芜花素、鼠李素进行了优化及单点能计算。从黄酮分子的几何构型、酚羟基H的NBO电荷数、不同位置酚羟基解离焓、HOMO和LUMO及其能级差分析所得:黄酮类化合物的羟基数目和形成的分子内氢键数目越多,抗氧化活性越强;不同位置酚羟基的活性不同,B环4’位酚羟基的活性最强,A环5位酚羟基的活性最弱,C环3位酚羟基的存在有利于鼠李素分子形成良好的共轭体系,提高了该化合物的抗氧化活性。结果表明,四种黄酮类化合物的抗氧化活性顺序为鼠李素>羟基芜花素>芜花素>芹菜素-7,4’二甲醚;文章最后对鼠李素分子清除羟基自由基的反应历程进行了动态模拟分析。     

蛋白质序列比对下的分子虚拟筛选方法

分子虚拟筛选方法旨在找到一种可以与受体蛋白质进行相互作用并适当修改其生物学行为的活性分子.大多数分子虚拟筛选方法的先决条件是已知蛋白质的结构或小分子结合物.然而对于大多数蛋白质而言,这些信息都是未知的.因此,本文提出了一种名为Screener的基于蛋白质序列比对和活性分子相似性评估的分子虚拟筛选方法.Screener首先从受体蛋白质的序列出发,生成位置特异性频率矩阵特征、二级结构特征以及溶剂可及性特征,利用I-LBR程序对受体蛋白质的潜在结合位点残基进行预测;其次,根据预测的结合位点残基以及相关特征信息构建模板蛋白质库;然后,将所有与任意模板蛋白质相互作用的活性分子收集起来构成潜在的种子分子库;最后,利用分子2D指纹之间的相似性来对待筛选分子集进行排序,完成分子虚拟筛选.在基准测试集DUD40和DUD-E65上,Screener的平均EF^1%分别为16.6和25.7,HR^1%分别为44.1和67.6.基准测试结果表明Screener的虚拟筛选平均性能优于基于对接的虚拟筛选方法AutoDock Vina及基于结构比对的虚拟筛选方法FINDSIT...     

流感病毒A型核酸内切酶与羟基嘧啶酮衍生物识别的分子动力学模拟

流感病毒A型核酸内切酶(Influenza A Endonuclease,IAE)是目前抗流感新药物研发的重要靶标。本文对IAE单体及其与羟基嘧啶酮衍生物(Hydroxy pyrimidine-ketone derivatives,HPD)抑制剂的复合物分别进行了2.1 ns的分子动力学模拟。从能量角度详细分析了IAE与HPD识别的关键残基,并对IAE-HPD复合物和IAE单体进行了成簇和自由能曲面计算,得到了HPD结合导致IAE的构象变化,主要是H41~Y48段α螺旋的去螺旋化以及H41等氨基酸残基的空间结构变化。优化后的结合模式表明,HPD与IAE识别主要是依靠一个双金属螯合的作用力以及周围残基的范德华相互作用力。模拟结果对于更深入理解IAE的结构特点以及与HPD的分子识别机制具有指导意义,为后续基于结构的抗流感病毒药物设计具有参考作用。     

姜黄素衍生物对乙醛脱氢酶1的活性抑制及构象关系研究

该研究测试了姜黄素及姜黄素衍生物对乙醛脱氢酶1(ALDH1)的体外抑制活性。结果表明大部分化合物对ALDH1具有较好的抑制作用,其中化合物A2对乙醛脱氢酶1的抑制作用最强,IC_(50)为8.2μmol/L,与对照物二硫仑(IC_(50)2.91μmol/L)的抑制活性在同一数量级,且比姜黄素(36.9μmol/L)的活性高4.5倍。通过Surflex-dock对姜黄素衍生物与ALDH1的分子对接相互作用研究,发现母体为戊二烯酮结构的化合物,当增加两端苯环的氢键受体和吸电子取代基,以及增加戊二烯酮母体结构的氢键供体及疏水性时,抑制活性增强。姜黄素及其衍生物可成为ALDH1的新型抑制剂。     

VEGF-B与去甲斑蝥素相互作用的分子动力学研究

利用分子对接(Molecular docking)结合分子动力学(Molecular dynamics,MD)模拟方法,建立去甲斑蝥素(Norcantharidin,NCTD)与血管内皮生长因子B(Vascular endothelial growth factor B,VEGF-B)的相互作用模型,分析二者的结合方式,结合能力,探究NCTD与VEGF-B的相互作用机制。结果表明,分子对接生成稳定的NCTD/VEGF-B复合物,NCTD与VEGF-B蛋白主链的Tyr117,Cys156,Gln46形成了氢键。经4ns的MD模拟后,NCTD/VEGF-B复合物体系达到了平衡,分析动力学轨迹并计算结合自由能证明了NCTD与VEGF-B的结合稳定合理。氢键、静电作用和疏水性为NCTD与VEGF-B稳定结合的主要贡献。本工作模建结果对开展NCTD抑制VEGF-B活性来控制肿瘤发生具有一定的理论意义。     

三氨基胍与乙二醛反应相互作用能的理论研究

采用量子化学方法详细计算了三氨基胍与乙二醛反应中各分子的结构,反应相互作用能。计算结果表明,反应过程中A分子中2个亚氨基上的氮原子分别与B分子中的2个碳原子结合形成一个咪唑烷五员环,同时,原来B分子中的碳原子由sp~2杂化转变为sp~3杂化。反应过程中A和B分子由于结构变化造成的分子能量增量之和小于A和B分子相互作用(吸引)能的绝对值,因此,A和B分子可以结合生成C分子。     

姜黄素类似物与酪氨酸酶相互作用的分子对接研究及应用

运用Surflex-dock对姜黄素类似物与酪氨酸酶的相互作用进行了分子对接研究,分析了小分子和受体的结合模式,阐述了其构效关系.对接结果表明,活性良好的化合物结合到酪氨酸酶的双核铜离子活性中心,计算结果与活性测试结果基本一致.运用该分子对接模型进行新型抑制剂设计,筛选出活性更强的带邻二酚羟基的姜黄素类似物,并得到实验...     

环氧酶/5-脂氧酶双重抑制剂的定量构效关系研究

目的:寻找COX/5-LO双重抑制剂的生物活性与化学结构之间的关系,为设计合成新型COX/5-LO双重抑制剂提供理论依据。方法:选择16个活性较强的COX/5-LO双重抑制剂,利用CNDO/2程序进行化合物的量子化学参数计算以及定量构效关系研究。结果:这些化合物对5-LO的抑制作用主要与LUMO和HOMO本征值之差以及分子偶极矩呈正相关;抑制COX作用主要与电子总能量呈负相关,与分子总能量和分子偶极矩呈正相关。结论:增加分子偶极矩,有可能同时增强COX/5-LO双重抑制作用,从而得到高效低毒的非甾体抗炎药。     

Isolation and in silico evaluation of antidiabetic molecules of Cynodon dactylon (L.)

Cynodon dactylon is a potential source of metabolites such as flavanoids, alkaloids, glycosides and β-sitosterol and has been traditionally employed to treat urinary tract and other microbial infections and dysentery. The present work attempts to evaluate the activity of C. dactylon extracts for glycemic control. Aqueous extracts of C. dactylon analyzed by HPLC–ESI MS have identified the presence of apigenin, luteolin, 6-C-pentosyl-8-C-hexosyl apigenin and 6-C-hexosyl-8-C-pentosyl luteolin. Evaluation of hypoglycemic activity through an extensive in silico docking approach with PPARγ (Peroxisome Proliferator-Activated Receptor), GLUT-4 (glucose transporter-4) and SGLT2 (sodium glucose co-transporter-2) revealed that luteolin, apigenin, 6-C-pentosyl-8-C-hexosyl apigenin, 6-C-hexosyl-8-C-pentosyl luteolin interact with SGLT2. Interactions of these molecules with Gln 295 and Asp 294 residues of SGLT2 have been shown to compare well with that of the phase III drug, dapagliflozin. These residues have been proven to be responsible for sugar sensing and transport. This work establishes C. dactylon extract as a potential SGLT2 inhibitor for diabetic neuropathy thus enabling a possibility of this plant extract as a new alternative to existing diabetic approaches.     

Allosteric pocket of the dengue virus (serotype 2) NS2B/NS3 protease: In silico ligand screening and molecular dynamics studies of inhibition

The allosteric pocket of the Dengue virus (DENV2) NS2B/NS3 protease, which is proximal to its catalytic triad, represents a promising drug target (Othman et al., 2008). We have explored this binding site through large-scale virtual screening and molecular dynamics simulations followed by calculations of binding free energy. We propose two mechanisms for enzyme inhibition. A ligand may either destabilize electronic density or create steric effects relating to the catalytic triad residues NS3-HIS51, NS3-ASP75, and NS3-SER135. A ligand may also disrupt movement of the C-terminal of NS2B required for inter-conversion between the “open” and “closed” conformations. We found that chalcone and adenosine derivatives had the top potential for drug discovery hits, acting through both inhibitory mechanisms. Studying the molecular mechanisms of these compounds might be helpful in further investigations of the allosteric pocket and its potential for drug discovery.     

Is the smartphone a smart choice? The effect of smartphone separation on executive functions

Despite a huge spike in smartphone overuse, the cognitive and emotional consequences of smartphone overuse have rarely been examined empirically. In two studies, we investigated whether separation from a smartphone influences state anxiety and impairs higher-order cognitive processes, such as executive functions. We found that smartphone separation causes heightened anxiety, which in turn mediates the adverse effect of smartphone separation on all core aspects of executive functions, including shifting (Experiment 1) and inhibitory control and working-memory capacity (Experiment 2). Interestingly, impaired mental shifting was evident regardless of the extent of smartphone addiction, whereas smartphone addiction significantly moderated the negative effect of smartphone separation on inhibitory control, as assessed by the Stroop task. The study sheds light on cognitive mechanisms that may underlie some of these negative consequences of smartphone overuse.     

Extraction of salient contours from cluttered scenes

The responses of neurons in the primary visual cortex (V1) to stimulus inside the receptive field (RF) can be markedly modulated by stimuli outside the classical receptive field. The modulation, relying on contextual configurations, yields excitatory and inhibitory activities. The V1 neurons compose a functional network by lateral interactions and accomplish specific visual tasks in a dynamic and flexible fashion. Well-organized structures and conspicuous image locations are more salient and thus can pop out perceptually from the background. The excitatory and inhibitory activities give different visual physiological interpretations to the two kinds of saliencies.A model of contour extraction, inspired by visual cortical mechanisms of perceptual grouping, is presented. We unify the dual processes of spatial facilitation and surround inhibition to extract salient contours from complex scenes, and in this way coherent spatial configurations and region boundaries could stand out from their surround. The proposed method can selectively retain object contours, and meanwhile can dramatically reduce non-meaningful elements resulting from a texture background. This work gives a clear understanding for the roles of the inhibition and facilitation in grouping, and provides a biologically motivated computational strategy for contour extraction in computer vision.     

Generalization in interactive networks: the benefits of inhibitory competition and Hebbian learning

Computational models in cognitive neuroscience should ideally use biological properties and powerful computational principles to produce behavior consistent with psychological findings. Error-driven backpropagation is computationally powerful and has proven useful for modeling a range of psychological data but is not biologically plausible. Several approaches to implementing backpropagation in a biologically plausible fashion converge on the idea of using bidirectional activation propagation in interactive networks to convey error signals. This article demonstrates two main points about these error-driven interactive networks: (1) they generalize poorly due to attractor dynamics that interfere with the network's ability to produce novel combinatorial representations systematically in response to novel inputs, and (2) this generalization problem can be remedied by adding two widely used mechanistic principles, inhibitory competition and Hebbian learning, that can be independently motivated for a variety of biological, psychological, and computational reasons. Simulations using the Leabra algorithm, which combines the generalized recirculation (GeneRec), biologically plausible, error-driven learning algorithm with inhibitory competition and Hebbian learning, show that these mechanisms can result in good generalization in interactive networks. These results support the general conclusion that cognitive neuroscience models that incorporate the core mechanistic principles of interactivity, inhibitory competition, and error-driven and Hebbian learning satisfy a wider range of biological, psychological, and computational constraints than models employing a subset of these principles.     

Contour detection based on a non-classical receptive field model with butterfly-shaped inhibition subregions

Physiological studies show that the response of classical receptive field (CRF) to visual stimulus could be suppressed by non-classical receptive field (NCRF) inhibition of the neurons in primary visual cortex (V1) and most of CRFs and NCRFs in V1 are orientation-selective. In addition, surround inhibition is normally spatially asymmetric. Inspired by these visual mechanisms, we proposed a feasible contour detection method based on an improved orientation-selective inhibition model in this paper. A butterfly-formed surrounding area is employed for the computation of inhibition term, and only one side subregion that produces less inhibition contributes to cell's response, which could provide a flexible inhibitory effect for the NCRF modulation on CRF. Comparisons with other visual contour detection models show that the proposed model can suppress texture effectively while retaining contours as much as possible.     

A computational model of lateralization and asymmetries in cortical maps

While recent experimental work has defined asymmetries and lateralization in left and right cortical maps, the mechanisms underlying these phenomena are currently not established. In order to explore some possible mechanisms in theory, we studied a neural model consisting of paired cerebral hemispheric regions interacting via a simulated corpus callosum. Starting with random synaptic strengths, unsupervised (Hebbian) synaptic modifications led to the emergence of a topographic map in one or both hemispheric regions. Because of uncertainties concerning the nature of hemispheric interactions, both excitatory and inhibitory callosal influences were examined independently. A sharp transition in model behavior was observed depending on callosal strength. For excitatory or weakly inhibitory callosal interactions, complete and symmetric mirror-image maps generally appeared in both hemispheric regions. In contrast, with stronger inhibitory callosal interactions, partial to complete map lateralization tended to occur, and the maps in each hemispheric region often became complementary. Lateralization occurred readily toward the side having a larger cortical region or higher excitability. Asymmetric synaptic plasticity, however, had only a transitory effect on lateralization. These results support the hypotheses that interhemispheric competition occurs, that multiple underlying asymmetries may lead to function lateralization, and that the effects of asymmetric synaptic plasticity may vary depending on whether supervised or unsupervised learning is involved. To our knowledge, this is the first computational model to demonstrate the emergence of topographic map lateralization and asymmetries.     

TIBO类衍生物抗HIV-1活性与电子结构关系的研究

应用分子力学MM＋方法，半经验量子化学MNDO计算了19个TIBO HIV－1逆转录酶抑制剂的优势构象和电子结构，得到了其抗HIV－1活性与电子结构的定量构效关系。结果表明：（1）TIBO类衍生物的体积越大、极性越小，即疏水性越大对抑制HIV－1活性越有利；（2）化合物中存在较大的正电区域，当C2原子连接吸电性基团时对药物的活性有利。     

Asynchronous states and the emergence of synchrony in large networks of interacting excitatory and inhibitory neurons

We investigate theoretically the conditions for the emergence of synchronous activity in large networks, consisting of two populations of extensively connected neurons, one excitatory and one inhibitory. The neurons are modeled with quadratic integrate-and-fire dynamics, which provide a very good approximation for the subthreshold behavior of a large class of neurons. In addition to their synaptic recurrent inputs, the neurons receive a tonic external input that varies from neuron to neuron. Because of its relative simplicity, this model can be studied analytically. We investigate the stability of the asynchronous state (AS) of the network with given average firing rates of the two populations. First, we show that the AS can remain stable even if the synaptic couplings are strong. Then we investigate the conditions under which this state can be destabilized. We show that this can happen in four generic ways. The first is a saddle-node bifurcation, which leads to another state with different average firing rates. This bifurcation, which occurs for strong enough recurrent excitation, does not correspond to the emergence of synchrony. In contrast, in the three other instability mechanisms, Hopf bifurcations, which correspond to the emergence of oscillatory synchronous activity, occur. We show that these mechanisms can be differentiated by the firing patterns they generate and their dependence on the mutual interactions of the inhibitory neurons and cross talk between the two populations. We also show that besides these codimension 1 bifurcations, the system can display several codimension 2 bifurcations: Takens-Bogdanov, Gavrielov-Guckenheimer, and double Hopf bifurcations.