多巴胺D1和D5受体的同源模建研究

多巴胺与其受体组成的多巴胺系统与许多疾病有关,比如帕金森病、精神分裂症等.但是,多巴胺受体的晶体结构一直没有得到解析,给相关疾病的药物开发带来难度.本文采用同源模建的方法,用与D1和D5受体同源性达到34.6%的肾上腺素能受体2vt4作为模板,构建D1和D5受体的三维模型.结果表明:经过优化和动力学模拟,然后用PROCHECK、ERRAT及PROSA程序进行构象和能量的评价,用多巴胺进行对接验证,证明模建的D1受体和D5受体模型是合理的、可靠的.     

抗药物依赖药效团模型的构建与虚拟筛选

运用计算机辅助药物设计方法,基于多巴胺D2和D3受体部分激动剂构建具有抗药物依赖功效的药效团模型。再以该药效团模型作为提问结构,在天然产物数据库中进行虚拟筛选,利用分子对接技术,对筛选结果进行分析和评价,初步得到具有抗药物依赖功效的目标化合物。最后对目标化合物进行虚拟水溶性、肠道吸收性和血脑屏障通透性研究,为抗药物依赖新药的研发提供理论基础。     

乙酰胆碱M3受体拮抗剂的从头设计

M3受体是人体内分布广泛的一种重要的毒蕈碱乙酰胆碱受体亚型,与膀胱过度活动症、心律失常、呼吸道及支气管疾病密切相关.设计与合成M3受体拮抗剂对于开发治疗相关疾病的药物具有重要理论意义和应用价值。本文采用同源模建方法,构建了人M3受体蛋白的三维结构,基于M3受体拮抗剂的结构构建了其药效团模型,其中较理想的模型含有6个药效团特征元素。利用药效团模型进行了虚拟筛选,虚拟筛选的数据库是本实验室构建的虚拟化合物库,发现了10个新型的对M3受体有拮抗作用的化合物。最后对这10个化合物进行了分子对接,根据对接结果,发现3个化合物对接能量及结合方式比较合理,为M3受体拮抗剂的合成研究及活性测定奠定了基础。     

整合素α_vβ_3受体配体的计算机辅助设计

肿瘤血管生成是肿瘤生长、浸润和转移过程中不可缺少的生物过程,整合素α_vβ_3对肿瘤血管生成起着重要作用。研发具有高亲和力和高特异性的整合素α_vβ_3受体配体在针对肿瘤血管生成进行靶向诊断与靶向治疗中具有重要意义。计算机辅助药物设计技术的问世,极大地推动了新型整合素α_vβ_3受体配体的研发。整合素α_vβ_3受体细胞外区X射线晶体衍射结构的获得为针对整合素α_vβ_3受体的药物设计奠定了基础。计算机辅助药物设计包括基于分子对接法(Docking)的直接药物设计和基于药效团的间接药物设计,Docking可预测配体-蛋白的相互作用、对受体-配体结合进行三维构效关系研究、设计具有高亲和力与选择性的新型配体。通过将小分子数据库与α_vβ_3受体(PDB号为1L5G)进行对接,筛选出具有较高亲和力的α_vβ_3受体拮抗剂-3(3-吡啶基)-3-[4-[2-(5,6,7,8-四氢[1,8]萘啶-2)乙基]吲哚-1]丙酸和3,4-二氯苯基双胍,后者与目前已知的配体具有不同的受体结合模式。在间接药物设计中,提出了以Arg的带正电荷的侧链、Asp的带负电荷的侧链和Gly的疏水基团为药效团特征的三点药效团模型和以氢键供体、氢...     

一种用SMILES码构建虚拟组合化学库的新方法

提出了一种利用SMILES码构建虚拟组合化学库的新方法。该方法用SMILES码代表骨架和侧链,通过对其进行排列组合生成虚拟组合化学库。用户可设定ADME筛选条件对生成的库进行初筛,以舍弃在理论上药代动力学行为不好的分子。该法通过构建一个抗2型糖尿病药物虚拟组合化学库(A2DDVCL)而得到了验证。A2DDVCL建立在过氧化物酶增殖体活化受体(PPAR)配体的基础上,拟从其中发现治疗慢性代谢疾病特别是2型糖尿病的药物。     

多巴胺D2受体抑制剂定量构效关系的研究

利用HyperChem软件包中的AM1半经验量子化学算法,将58个多巴胺D2受体抑制剂,作几何结构优化和计算,选取一些可能会影响及pIC_(50)值的26个理化和电子结构参数,作为描述分子的变量研究QSAR,利用偏最小二乘(PLS),穷举回归(QLS)及人工神经网络法(CGANN),以建立物理化学和电子结构等参数与其抑制活性之间的QSAR模型。结果表明:当化合物R_3位的疏水参数较大,R_5位疏水参数较小时抑制多巴胺D_2受体的能力较大,苯环上有硝基取代时不利于增加抑制活性。当该类化合物偶极矩较小,分子表面积较小、电子能较小,则有利于提高化合物的抑制活性。     

GPR109A同源建模及其与吡唑类激动剂对接模拟

烟酸受体G偶联蛋白受体109A(GPR109A)是心血管疾病和脂代谢紊乱等疾病治疗的重要靶点蛋白,但因属于膜蛋白,其晶体结构一直未被解析,给药物设计带来极大挑战。本文基于鼠类PUMA-G晶体结构,采用同源模建的方法构建GPR109A蛋白三维结构,运用Ramachandran Plot和Profile-3D对模型进行评估,通过加力场,加膜,loop等方法对模型进行优化,得到蛋白最优模型,并计算分析得到其12个可能的活性位点。利用SYBYL-X2软件构建GPR109A的吡唑类激动剂药物小分子,通过最陡下降法和共轭梯度法得到药物小分子的最稳定构象。用Libdock方法将激动剂对接至蛋白各活性位点,获得二者作用模型。我们分析各活性位点氨基酸分布情况,并以3-羧酸5-甲基吡唑为参考分子探讨药物与各蛋白活性位点相互作用情况。本实验对设计G偶联蛋白受体109A吡唑类激动剂有理论指导意义。     

β-受体阻滞剂在慢性心力衰竭治疗中的应用

β-受体阻滞剂治疗心力衰竭(心衰)已积累了较丰富的经验。随着对心衰发生机理的研究和治疗模式的转变,β-受体阻滞剂逐渐成为继强心、利尿、扩血管药物治疗心衰之后的第4类重要药物。1β-受体阻滞剂治疗心衰的机理1.1β-受体上调作用慢性心衰(CHF)时常伴β-受体密度下调,重度心衰时β-1受体密度下调60%-70%。β-受体阻滞剂可使β-受体密度增加,恢复β-受体对交感神经系统的敏感性。     

静电自组装技术制备多巴胺传感器的研究

利用静电自组装技术研制一种多巴胺传感器.以高纯度Pt丝为基体,利用壳聚糖(chitosan)结合静电自组装方法固定酪氨酸酶(tyrosinase),再修饰Nafion膜,制备复合膜修饰的新型多巴胺传感器,并用该传感器监测给药后大鼠尾核中多巴胺浓度.测试结果显示:传感器线性范围为5×10-7～5×10-4 mol/L,R2=0.9961;重复性误差为3.43%;给药后,该传感器检测结果显示多巴胺浓度与药物剂量间存在相关性,达峰时间为40～45 min.该传感器具有良好的选择性、稳定性和重现性;在体测定结果表明:该传感器可用于在体监测多巴胺的实验研究.     

尿道选择性α_1-肾上腺素受体拮抗剂药效团的构建

目的 :建立具有尿道选择性α1 肾上腺素受体拮抗剂的药效团模型。方法 :选择对受体亚型和尿道组织均有高亲和力的化合物 ,经计算机建模、分子动力学优化、系统搜索得到一系列低能构象 ,通过Apex 3D软件计算并构建药效团初步模型 ,再参照已有的构效关系数据进行筛选、判别。结果 :得到 3个符合要求的药效团 ,它们均含有一个碱性中心和芳环中心 ,还存在一个氢位点 (HST)。结论 :该模型有助于我们设计、合成活性高且副作用低的新型抗前列腺增生药物。     

Shape from silhouette outlines using an adaptive dandelion model

In this paper we study the problem of shape from silhouette outlines (SFO) using a novel adaptive dandelion model. SFO reconstructs a 3D model using only the outmost silhouette contours and produces a solid called the “bounding hull”. The dandelion model is composed of a pencil of organized line segments emitted from a common point which samples the bounding hull surface in regularly distributed orientations with the ending points serving as sampling points. The orientations and the topology of the line segments are derived from a geodesic sphere. The lengths of the line segments are computed by cutting rays in 2D with silhouette outlines. Based on the subdivision structure of the geodesic sphere, the sampling resolution can be refined adaptively until the desired precision is achieved. Finally a manifold mesh is extracted from the dandelion model.     

Computational study of human phosphomannose isomerase: Insights from homology modeling and molecular dynamics simulation of enzyme bound substrate

Phosphomannose isomerase is a zinc metalloenzyme that catalyzes the reversible isomerization of mannose-6-phosphate and fructose-6-phosphate, and the three-dimensional (3D) structure of human phosphomannose isomerase has not been reported. In order to understand the catalytic mechanism, the 3D structure of the protein is built by using homology modeling based on the known crystal structure of mannose-6-phosphate isomerase from (PDB code 1PMI). The model structure is further refined by energy minimization and molecular dynamics methods. The mannose-6-phosphate-enzyme complex is developed by molecular docking and the key residues involved in the ligand binding are determined, which will facilitate the understanding of the action mode of the ligands and guide further genetic studies. Our results suggest a hydride transfer mechanism of alpha-hydrogen between the C1 and C2 positions but do not support the cis-enediol mechanism. The detailed mechanism involves, on one side, Zn2+ mediating the movement of a proton between O1 and O2, and, on the other side, the hydrophobic environment formed in part by Tyr278 promoting transfer of a hydride ion.     

CASC2D分布式水文模型异构并行算法研究

针对 CASC2D 模型精细化水文模拟时面临的计算耗时长、效率低等问题,在保持产汇流算法和流域拓扑结构的基础上,采用 CPU+GPU 的异构并行算法对 CASC2D 模型程序进行重新设计和优化,模型程序中的降雨、 产流、坡面汇流和河道汇流过程均优化为并行计算,以提高 CASC2D 模型的计算效率。将优化后的 CASC2D 模型应用于前毛庄流域的洪水流量过程模拟,计算结果与原 CASC2D 模型保持一致。在栅格分辨率为 30 m,计算步长为 3 s 时,与原 CPU 串行计算方法相比,并行加速比达到 34 倍以上,并且栅格单元数据精度越高,加速比提升越明显。异构并行算法可在不降低模拟精度的条件下显著提升 CASC2D 模型的计算效率,满足实时水文预报的应用需求。     

Joint reversible watermarking and progressive compression of 3D meshes

A new reversible 3D mesh watermarking scheme is proposed in conjunction with progressive compression. Progressive 3D mesh compression permits a progressive refinement of the model from a coarse to a fine representation by using different levels of detail (LoDs). A reversible watermark is embedded into all refinement levels such that (1) the refinement levels are copyright protected, and (2) an authorized user is able to reconstruct the original 3D model after watermark extraction, hence reversible. The progressive compression considers a connectivity-driven algorithm to choose the vertices that are to be refined for each LoD. The proposed watermarking algorithm modifies the geometry information of these vertices based on histogram bin shifting technique. An authorized user can extract the watermark in each LoD and recover the original 3D mesh, while an unauthorized user which has access to the decompression algorithm can only reconstruct a distorted version of the 3D model. Experimental results show that the proposed method is robust to several attack scenarios while maintaining a good compression ratio.     

三维实体仿真建模的网格自动生成方法

有限元网格模型的生成与几何拓扑特征和力学特性有直接关系。建立网格模型时，为了更真实地反映原几何形体的特征，在小特征尺寸或曲率较大等局部区域网格应加密剖分；为提高有限元分析精度和效率，在待分析的开口、裂纹、几何突变、外载、约束等具有应力集中力学特性的局部区域，网格应加密剖分。为此，该文提出了基于几何特征和物理特性相结合的网格自动生成方法。该方法既能有效地描述几何形体，又能实现应力集中区域的网格局部加密及粗细网格的均匀过渡。实例表明本方法实用性强、效果良好。     

A computational model of bounded developable surfaces with application to image‐based three‐dimensional reconstruction

Developable surfaces have been extensively studied in computer graphics because they are involved in a large body of applications. This type of surfaces has also been used in computer vision and document processing in the context of three‐dimensional (3D) reconstruction for book digitization and augmented reality. Indeed, the shape of a smoothly deformed piece of paper can be very well modeled by a developable surface. Most of the existing developable surface parameterizations do not handle boundaries or are driven by overly large parameter sets. These two characteristics become issues in the context of developable surface reconstruction from real observations. Our main contribution is a generative model of bounded developable surfaces that solves these two issues. Our model is governed by intuitive parameters whose number depends on the actual deformation and including the “flat shape boundary”. A vast majority of the existing image‐based paper 3D reconstruction methods either require a tightly controlled environment or restricts the set of possible deformations. We propose an algorithm for reconstructing our model's parameters from a general smooth 3D surface interpolating a sparse cloud of 3D points. The latter is assumed to be reconstructed from images of a static piece of paper or any other developable surface. Our 3D reconstruction method is well adapted to the use of keypoint matches over multiple images. In this context, the initial 3D point cloud is reconstructed by structure‐from‐motion for which mature and reliable algorithms now exist and the thin‐plate spline is used as a general smooth surface model. After initialization, our model's parameters are refined with model‐based bundle adjustment. We experimentally validated our model and 3D reconstruction algorithm for shape capture and augmented reality on seven real datasets. The first six datasets consist of multiple images or videos and a sparse set of 3D points obtained by structure‐from‐motion. The last dataset is a dense 3D point cloud acquired by structured light. Our implementation has been made publicly available on the authors' web home pages. Copyright © 2012 John Wiley & Sons, Ltd.     

Estimation of Volumetric Oxygen Concentration in a Marine Environment with an Autonomous Underwater Vehicle

Dissolved oxygen (DO) concentration is a key indicator of the health and productivity of an aquatic ecosystem. This paper presents a new method for high‐resolution characterization of DO as a function of both space and time. The implementation of a new oxygen optode in an Iver2 autonomous underwater vehicle (AUV) is described, which enables the system to measure both absolute oxygen concentration and percentage saturation. Also described are details of AUV missions in Hopavågen Bay, Norway, which consisted of a series of repeated undulating lawnmower patterns that covered the bay. Through offline postprocessing of data, sensor characteristic models were developed, as well as a 3D lattice time series model. The model was constructed by estimating DO at each 3D lattice node location using a 1D Kalman filter that fused local measurements obtained with the AUV. By repeating model construction for several missions that spanned 24 h, estimates of DO as a function of space and time were calculated. Results demonstrated (1) the AUVs ability to repeatedly gather high‐spatial‐resolution data (2) significant spatial and temporal variation in DO in the water body investigated, and (3) that a 3D model of DO provides better estimates of total DO in a volume than extrapolating from only a single 2D plane. Given the importance of oxygen within an ecosystem, this new method of estimating the quantity of DO per volume has the potential to become a reliable test for the health of an underwater ecosystem. Also, it can be refined for detecting and monitoring a range of soluble gases and dispersed particles in aquatic environments, such as dissolved O₂ and CO₂ around production facilities such as fish farms, or dispersed hydrocarbons and other pollutants in fragile ecosystems. © 2012 Wiley Periodicals, Inc.     

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。