N-取代-4-取代苯基哌嗪-1-乙酰胺类α1-肾上腺素受体拮抗剂的三维定量构效关系研究

寻找α1-肾上腺素受体拮抗剂化学结构与生物活性之间的关系，为设计新的α1-受体拮抗剂提供理论依据，对28个N-取代-4-取代苯基哌嗪-1-乙酰胺类α1-受体拮抗剂，以自组织分子场分析法进行了三维定量构效关系研究。结果表明，最优SOMFA模型得到交叉验证相关系数q^2为0．733，回归系数r^2为0．740，建立的3D-QSAR模型应有一定的活性预测能力。     

苯并呋喃类组胺H_3受体拮抗剂的构效关系研究

绢胺H3受体在体内参与调节很多神经递质的释放.人们预期,H3受体拮抗剂将临床应用于老年性痴呆症、抑郁症、精神分裂症等中枢性疾病.本文使用三维定量构效关系研究方法,包括比较分子场分析法(CoMFA)和比较分子相似性指数分析法(CoMSIA),研究芳基苯并呋喃类H3受体拮抗剂的分子结构与生物活性之间的定量关系.本文使用CoMSIA法所获建三维定量构效关系模型,其交叉验证系数q2为0.646,非交叉验证相关系数R2为0.920,表明模型预测能力较好,同时使用"留八法"证实模型的稳定和可靠.模型中各分子场的贡献为:立体场10.4%、静电场56.9%和疏水场32.7%.三维系数等势图和静电势图显示:母核3'和4'位上的取代基对活性影响较大,估计它们是配体与受体作用的位点.本研究结果可为设计和开发活性更高的该类拮抗剂提供理论参考.     

GABAA/BZ受体激动剂4-喹啉酮衍生物的DISCOtech及CoMFA研究

γ-氨基丁酸是重要的抑制性神经传递物质,4-喹啉酮衍生物作用于GABAA受体具有广泛的生物活性.本文采用DIS-COtech法构建大鼠GABAA/BZ受体4-喹啉酮衍生物激动剂的药效团模型,同时根据分子骨架叠合规则构建CoMFA模型,模型的交叉验证系数为0.681,非交叉验证系数为0.967,药效团模型和CoMFA模型具有一致性.根据模型分析配体-受体间的相互作用,设计一系列化合物并预报了其活性,为设计高活性的化合物提供参考.     

比较分子力场法研究5,6-二氢-(9H)-吡唑[3,4-c]-1,2,4-三唑[4,3-a]吡啶类抑制剂的定量构效关系

利用比较分子力场分析法(CoMFA),以5,6-二氢-(9H)-吡唑[3,4-c]-1,2,4一三唑[4,3-a]吡啶类抑制剂为研究对象,建立一组对嗜酸性粒细胞磷酸二酯酶有抑制活性的化合物及其三维定量构效关系(3D-QSAR)模型,探索化合物活性数据和三维结构参数之间的关系.模型的交叉验证相关系数q2=0.565,非交叉验证相关系数r2=0.867,标准偏差SE=0.362,F=49.782,立体场和静电场的贡献值分别为72.7%和27.3%.该模型的预测能力较好,能够增大取代基体积和降低取代基电负性,可以提高该类化合物的活性.     

二苯基吡咯烷酮类5-HT_(2C)抑制剂三维定量构效关系的研究

目前在药物设计开发领域,5-HT2C受体抑制剂备受关注,本文用比较分子相似性指数分析法(CoMSlA),研究34个二苯基取代吡咯烷酮类化合物的三维定量构效关系.考察衰减因子、电荷计算法以及不同作用场对构建模型的影响.建立的最佳模型交叉验证相关系数(q2)为0.571,非交叉验证相关系数(R2)为0.929,模型的标准偏差为0.225.发现疏水性在该类化合物与受体相互作用中发挥至关重要的作用,为进一步修饰结构提供指导.     

N,N-二甲基-2-溴苯乙胺类衍生物活性与CoMFA、CoMSIA的研究

用比较分子力场分析(CoMFA)法和比较分子相似性指数分析(CoMSIA)法,建立N,N-二甲基-2-溴苯乙胺类化合物的3D-QSAR模型。CoMFA模型中,其交叉验证系数q2=0．792,传统的相关系数R2=0．955(R=0．978),相应立体场贡献为77．4％、静电场贡献为22．6％,优于文献的报导。CoMSIA研究中,其交叉验证系数q2=0．757,传统的相关系数R2=0．917 (R=0．958),其疏水场、立体场、静电场贡献依次为:42．9％、39．5％、17．6％。用两种模型分别预测检测集分子的活性,结果与实验值较吻合。说明所建的模型具有较好的预测能力。通过分析CoMFA分子场等值线图,可为优化N,N-二甲基-2-溴苯乙胺类衍生物的结构提供理论指导。     

DNA依赖蛋白激酶抑制剂的CoMFA研究

运用比较分子力场分析方法(CoMFA),以DNA依赖蛋白激酶(DNA-PK)抑制剂分子为研究对象,建立1组对DNA依赖蛋白激酶有抑制活性化合物的三维定量构效关系(3D-QSAR)模型,探索其活性数据和三维结构参数的关系,所建最佳模型交叉验证相关系数q2=0.670,非交叉验证相关系数R2=0.993,标准偏差SD=0.053,说明该模型预测能力较好.根据CoMFA模型的三维等势图可知,小体积、电负性大的取代基团,能提高该类化合物的活性,为新型DNA-PK抑制剂分子的设计提供了理论依据.     

对位二取代苯电离能中取代基效应的研究

本文以取代基电子效应加和项(∑σ_p),取代基相互作用项(△σ~2)和分子权重平均极化效应指数(WAPEI)为参数研究1,4-二取代苯电离能中取代基效应规律,成功得到111个1,4-二取代苯电离能的相关方程,其相关系数为0.9631,标准偏差仅为0.21eV。该方法为芳香化合物电离能的研究提供了一种新的思路。     

17α取代雌二醇与雌激素受体结合活性的定量构效关系研究

应用分子力学法MM+和半经验量子化学AM1法几何全优化得到29个17α取代雌二醇衍生物的优势构象,再利用量子化学法和分子图形学技术获得相应优势构象的电子结构参数和几何结构参数,采用多元线性回归分析研究17α取代雌二醇衍生物与雌激素受体结合活性(relative binding affinities)的定量构效关系.结果表明17α取代雌二醇衍生物与雌激素受体结合活性和分子键合能(BE)、17号碳原子的净电荷(Q)及7号和8号碳原子间键长的相关性较好,成功地建立了29个17α取代雌二醇衍生物的构效关系式,所建回归方程的复相关系数R2及去一法交互检验相关系数Rcv2分别为0.890和0.712.     

2,5-二酮哌嗪类微管蛋白抑制剂的3D-QSAR研究

微管蛋白对细胞增殖极为重要,现已成为抗癌药物研发的重要靶标之一。针对53个以2,5-二酮哌嗪为基本骨架的微管蛋白抑制剂,分别运用比较分子力场分析(CoMFA)以及比较分子相似性指数分析(CoMSIA)2种经典方法进行了三维定量构效关系(3D-QSAR)研究,并依次建立了相关的模型。CoMFA模型的交叉验证系数q~2为0.642,相关系数r~2为0.996:CoMSIA模型的q~2和r~2,分别为0.725,0.908。模型具有较好的预测能力和较强的稳定性。3D-QSAR模型三维等势图揭示了一些结构特征与抑制活性的关系。我们希望这些研究为该类药物今后的设计和筛选提供可靠的理论依据。     

The function of the amino terminal domain in NMDA receptor modulation

N-methyl-D-aspartate (NMDA) receptors are ligand-gated channels important in neurotransmission which are activated by the combined presence of glutamate and glycine. They are comprised of four subunits that form a dimer of dimers. The activity of NMDA receptors is modulated by a variety of endogenous ligands such as zinc ions, phenylethanolamines, polyamines and protons. Findings show that the binding sites for these modulators are found in the amino terminal domain of such receptors, but different modulators appear to affect different subunits. However, despite the enormous efforts expended in mutagenesis and patch clamp experiments on NMDA receptors, the exact assembly of these subunits and the effects of the modulatory species are not well understood. We have modelled dimers of the amino terminal domains of these receptors based on their homology with the extracellular dimer of a metabotropic glutamate receptor. Conserved cysteine residues, which have been highlighted as important in previous work, are shown to form a disulphide bridge, stabilizing a four-helix bundle between subunits. This establishes a hinge in the receptor. The model also highlights a zinc binding site in the binding crevice of the NR2a subunit of the receptor that stabilizes the open state of the amino terminal domain. The similar effect of ifenprodil is thus explained by its stabilization of the open state of the amino terminal domain (ATD). The presence of three histidine residues in the zinc site is used to explain the pH dependence of zinc inhibition. Previous work has also implicated certain residues in spermine stimulation of such receptors. The homology model shows that this site is found at the inter-subunit boundary of the dimer. This predicts a binding site between subunits, a result not calculable by the homology modelling of single subunits done previously. Finally, these results are drawn together to yield a consistent picture of NMDA receptor activation and desensitization. An understanding of how these receptors work and how they can be modulated is an important step toward rational drug design.     

Exploring putative inhibitors of Death Associated Protein Kinase 1 (DAPK1) via targeting Gly-Glu-Leu (GEL) and Pro-Glu-Asn (PEN) substrate recognition motifs

Recently, a new signaling complex Death Associated Protein Kinase 1 (DAPK1) ̶ N-methyl-D-aspartate receptor subtype 2B (NMDAR2B or NR2B) engaged in the neuronal death cascade was identified and it was found that after stroke injury, N-methyl-D-aspartate glutamate (NMDA) receptors interact with DAPK1 through NR2B subunit and lead to excitotoxicity via over-activation of NMDA receptors. An acute brain injury, such as stroke, is a serious life-threatening medical condition which occurs due to poor blood supply to the brain and further leads to neuronal cell death. During a stroke, activated DAPK1 migrates towards the extra-synaptic site and binds to NR2B subunit of NMDA receptor. It is this DAPK1-NR2B interaction that arbitrates the pathological processes like apoptosis, necrosis, and autophagy of neuronal cells observed in stroke injury, hence we aimed to inhibit this vital interaction to prevent neuronal damage. In the present study, using PubChem database, we applied an integrative approach of virtual screening and molecular dynamic simulations and identified a potential lead compound 11 that interrupts DAPK1-NR2B interaction by competing with both ATP and substrate for their binding sites on DAPK1. This inhibitor was found potent and considerably selective to DAPK1 as it made direct contact with the ATP binding sites as well as substrate recognition motifs: Gly-Glu-Leu (GEL) and Pro-Glu-Asn (PEN). Further in vitro and in vivo experiments are demanded to validate the efficacy of compound 11 nevertheless, it can be considered as suitable starting point for designing DAPK1 inhibitors.     

Computational investigation of the antagonism effect towards GluN2B-Containing NMDA receptor: Combined ligand-based and target-based approach

The interaction of GluN2B-Containing NMDA Receptor with 18 antagonists were investigated by a combined ligand-based and target-based approach. First, two distinct pharmacophore models were generated for antagonists which cluster in two groups with Catalyst (HipHop module). The pharmacophore of “ifenprodil group” antagonists includes three hydrophobic groups, one H-bond donor and one H-bond acceptor, the pharmacophore of “EVT101 group” antagonists involves one aromatic ring, two hydrophobic groups and one H-bond acceptor. Docking results and pharmacophore model confrontation allow the pharmacodynamic characteristics to be weighted and structural information integrated. Which results in the proposal of two interaction models inside the GluN2B binding cavity for two groups of antagonists. The interaction model of “ifenprodil group” antagonists consists of one hydrophobic group, one H-bond donor, one H-bond acceptor and an aromatic ring, while on the other hand, the interaction model of “EVT101 group” antagonists includes three hydrophobic groups and an aromatic ring.     

Properties of synaptic transmission and the global stability of delayed activity states

The influence of synaptic channel properties on the stability of delayed activity maintained by recurrent neural networks is studied. The duration of excitatory post-synaptic current (EPSC) is shown to be essential for the global stability of the delayed response. The NMDA receptor channel is a much more reliable mediator of the reverberating activity than the AMPA receptor, due to a longer EPSC. This allows one to interpret the deterioration of the working memory observed in NMDA channel blockade experiments. The key mechanism leading to the decay of the delayed activity originates in the unreliability of synaptic transmission. The optimum fluctuation of the synaptic currents leading to the decay is identified. The decay time is calculated analytically and the result is confirmed computationally.     

Neural bistability and amplification mediated by NMDA receptors: Analysis of stationary equations

The macroscopic current/voltage relationship of NMDA receptor ion channels is nonmonotonic under physiological conditions, which can give rise to bistable and amplifying/facilitatory behavior in neurons and neural structures, supporting significant computational primitives. Conditions under which bistable regimes of operation prevail, and also general amplifying properties associated with active NMDA receptors, are examined in a single compartment enclosed by a cell membrane, and subsequently in cable-like dendrites under varying boundary conditions. Methodology consists of numerical and mathematical analyses of stationary versions of equations governing the electrical behavior of these systems. Bistability mediated by NMDA receptors requires interaction with other conductances in the membrane or cytoplasm, with particular importance attached to membrane potassium conductance, especially that of inward-rectifying potassium channels. A corollary conclusion is that coactivation of GABA_B synaptic receptors or SK channels is a computationally powerful and sometimes necessary adjunct condition for NMDA receptor-mediated bistability. Neural multistability due to dendritic bistability is considered, including the case of closely coupled dendrites. The characteristics of coactivation-dependent facilitation, and amplifying states in which NMDA receptor activation boosts the efficacy of other classes of synapses, are also described. Coactive inward-rectifying potassium channels are found to significantly affect the characteristics of such amplification.     

Three-dimensional models of histamine H3 receptor antagonist complexes and their pharmacophore

Molecular modeling was used to analyze the binding mode and activities of histamine H₃ receptor antagonists. A model of the H₃ receptor was constructed through homology modeling methods based on the crystal structure of bovine rhodopsin. Known H₃ antagonists were interactively docked into the putative antagonist binding pocket and the resultant model was subjected to molecular mechanics energy minimization and molecular dynamics simulations which included a continuum model of the lipid bilayer and intra- and extracellular aqueous environments surrounding the transmembrane helices. The transmemebrane helices stayed well embedded in the dielectric slab representing the lipid bilayer and the intra- and extracellular loops remain situated in the aqueous solvent region of the model during molecular dynamics simulations of up to 200 ps in duration. A pharmacophore model was calculated by mapping the features common to three active compounds three-dimensionally in space. The 3D pharmacophore model complements our atomistic receptor/ligand modeling. The H₃ antagonist pharmacophore consists of two protonation sites (i.e. basic centers) connected by a central aromatic ring or hydrophobic region. These two basic sites can simultaneously interact with Asp 114 (3.32) in helix III and a Glu 206 (5.46) in helix V which are believed to be the key residues that histamine interacts with to stabilize the receptor in the active state. The interaction with Glu 206 is consistent with the enhanced activity resulting from the additional basic site. In addition to these two salt bridging interactions, the central region of these antagonists contains a lipophilic group, usually an aromatic ring, that is found to interact with several nearby hydrophobic side chains. The picture of antagonist binding provided by these models is consistent with earlier pharmacophore models for H₃ antagonists with some exceptions.     

Three-dimensional models of histamine H3 receptor antagonist complexes and their pharmacophore

Molecular modeling was used to analyze the binding mode and activities of histamine H₃ receptor antagonists. A model of the H₃ receptor was constructed through homology modeling methods based on the crystal structure of bovine rhodopsin. Known H₃ antagonists were interactively docked into the putative antagonist binding pocket and the resultant model was subjected to molecular mechanics energy minimization and molecular dynamics simulations which included a continuum model of the lipid bilayer and intra- and extracellular aqueous environments surrounding the transmembrane helices. The transmemebrane helices stayed well embedded in the dielectric slab representing the lipid bilayer and the intra- and extracellular loops remain situated in the aqueous solvent region of the model during molecular dynamics simulations of up to 200 ps in duration. A pharmacophore model was calculated by mapping the features common to three active compounds three-dimensionally in space. The 3D pharmacophore model complements our atomistic receptor/ligand modeling. The H₃ antagonist pharmacophore consists of two protonation sites (i.e. basic centers) connected by a central aromatic ring or hydrophobic region. These two basic sites can simultaneously interact with Asp 114 (3.32) in helix III and a Glu 206 (5.46) in helix V which are believed to be the key residues that histamine interacts with to stabilize the receptor in the active state. The interaction with Glu 206 is consistent with the enhanced activity resulting from the additional basic site. In addition to these two salt bridging interactions, the central region of these antagonists contains a lipophilic group, usually an aromatic ring, that is found to interact with several nearby hydrophobic side chains. The picture of antagonist binding provided by these models is consistent with earlier pharmacophore models for H₃ antagonists with some exceptions.     

Extended Study of the Classification of Dopamine Receptor Agonists and Antagonists using a TFS-based Support Vector Machine

We previously investigated the classification and prediction of dopamine D1 receptor agonists and antagonists using a topological fragment spectra (TFS)-based support vector machine (SVM), in which the dataset contained noise compounds that had no D1 receptor activity. This work extended the dataset to seven activity classes (dopamine D1, D2, and auto-receptor agonists, and D1, D2, D3, and D4 antagonists) and increased the noise ratio to ten times that of active compounds. In total, this study used 16,008 compounds for training and 1,779 compounds for prediction. The TFS-based SVM gave good, stable results for both classification and prediction, even in the case that included ten times the noise data. The resulting model correctly predicted 97.6% of the prediction set of 1,779 compounds.