抗病毒的寡糖药物

该文依据寡糖药物抗病毒机制,分别介绍阻止病毒黏附的糖序列模拟物,具有酶抑制剂活性的抗病毒寡糖及糖模拟物,刺激体内免疫作用的糖疫苗及其他一些机制方面抗病毒糖药物的研究进展。     

MiR-182模拟物提高1型糖尿病小鼠的心脏功能

目的探讨miR-182模拟物对1型糖尿病小鼠心脏功能的影响及可能作用机制。方法 40只8周龄雄性C57小鼠随机分为正常对照组(n=5),miR-182模拟物对照组(n=5),1型糖尿病组(n=15),1型糖尿病+miR-182模拟物治疗组(n=15)。腹腔注射链脲佐菌素(STZ)建立1型糖尿病动物模型。实验于8周末结束,采用小动物用高分辨超声仪测量小鼠心脏功能;运用透射电镜观察心肌组织超微结构改变;利用real-time PCR技术检测心肌组织β-肌球蛋白重链(β-MHC),α-肌球蛋白重链(α-MHC),心房钠尿肽(ANP),I型(Col I)和III型胶原(Col III)mRNA及miR-182 mRNA的表达含量。结果 1miR-182模拟物可改善1型糖尿病小鼠的心脏功能,增加心脏射血分数及左室短轴缩短率(P0.01);2miR-182模拟物可降低糖尿病小鼠心肌组织ANP、Col I、Col III的表达及β/a-MHC比值(P0.01);3miR182模拟物可改善1型糖尿病小鼠心肌超微结构变化,减轻自噬。结论MiR-182模拟物能改善1型糖尿病小鼠的心脏功能,其机制可能与减轻心肌肥大和心肌纤维化,减轻线粒体结构损伤及减轻自噬有关。     

基于量子进化算法的RNA序列-结构比对

多序列比对是计算分子生物学的经典问题,也是许多生物学研究的重要基础步骤．RNA作为生物大分子的一种,不同于蛋白质和DNA,其二级结构在进化过程中比初级序列更保守,因此要求在RNA序列比对中不仅要考虑序列信息,更要着重考虑二级结构信息．提出了一种基于量子进化算法的RNA多序列-结构比对程序,对RNA序列进行了量子编码,设计了考虑进结构信息的全交叉算子,提出了适合于进行RNA序列-结构比对的适应度函数,克服了传统进化算法收敛速度慢和早熟问题．在标准数据库上的测试,证实了方法的有效性．     

蛋白质二级结构预测方法的评价

目前评价蛋白质二级结构预测方法主要考虑预测准确率,并没有充分考虑方法自身参数对方法的影响。本文提出一种新型评价方法,将内在评价与外在评价相结合评价预测方法的优劣。以基于混合并行遗传算法的蛋白质二级结构预测方法为例,通过内在评价,合理选取内在参数——切片长度和组内类别数,有效提高预测准确率,同时,通过外在评价,与其他基于随机算法的蛋白质二级结构预测算法比较和与CASP所提供的结论比较,说明了方法的有效性与正确性,以此验证内在评价和外在评价的客观性、公正性和全面性。     

基于结构信息的RNA多序列比对

多序列比对是生物信息学中重要的基础研究内容,对各种RNA序列分析方法而言,这也是非常重要的一步。不像DNA和蛋白质,许多功能RNA分子的序列保守性要远差于其结构的保守性,因此,对RNA的分析研究要求其多序列比对不仅要考虑序列信息,而且要充分考虑到其结构信息。本文提出了一种考虑了结构信息的同源RNA多序列比对算法,它先利用热力学方法计算出每条序列的配对概率矩阵,得到结构信息,由此构造各条序列的结构信息矢量,结合传统序列比对方法,提出优化目标函数,采用动态规划算法和渐进比对得到最后的多序列比对。试验证实该方法的有效性。     

基于支持向量机分类的RNA共同二级结构预测

比较序列分析作为RNA二级结构预测的最可靠途径, 已经发展出许多算法。将基于此方法的结构预测视为一个二值分类问题: 根据序列比对给出的可用信息, 判断比对中任意两列能否构成碱基对。分类器采用支持向量机方法, 特征向量包括共变信息、热力学信息和碱基互补比例。考虑到共变信息对序列相似性的要求, 通过引入一个序列相似度影响因子, 来调整不同序列相似度情况下共变信息和热力学信息对预测过程的影响, 提高了预测精度。通过49组Rfam-seed比对的验证, 显示了该方法的有效性, 算法的预测精度优于多数同类算法, 并且可以预测简单的假节。     

基于FPGA的彩超信号处理中的壁滤波器设计与实现

目的:探索一种投影初始化无限冲激响应(ⅡR)壁滤波器的设计以及其在现场可编辑门阵列(FPGA)平台上的实现.方法:首先,利用矩阵实验室(Matlab)矩阵运算的优势,进行算法的仿真,通过对仿真结果的分析,初步评估该算法的有效性;其次,将算法进行理论上的优化,以使其能满足在硬件上运行的可行性;最后,根据现场可编辑门阵列(FPGA)的结构特点以及该算法的运算特点,提出了一种硬件运算结构来实现该滤波器算法.结果:这种投影初始化无限冲激响应(ⅡR)壁滤波器能充分利用可编辑门阵列(FPGA)并行运算的特点提高运算效率,并能有效的抑制人体内反射回来的杂波信号,提取出了血流的多普勒频移.结论:投影初始化无限冲激响应(ⅡR)壁滤波器在现场可编辑门阵列(FPGA)里得到了实现.     

利用粒子群算法在菱形网格上预测蛋白质结构

本文在菱形网格上研究讨论了二维HP模型。首先,将蛋白质结构预测问题转化成一个数学问题,并简化成氨基酸序列中每个氨基酸与网格格点的匹配问题。为了解决这个数学问题,我们改进并扩展了经典的粒子群算法。为了验证算法和模型的有效性,我们对一些典型的算例进行数值模拟。通过与方格网上得到的蛋白质构象进行比较,菱形网上的蛋白质构象更自然,更接近真实。我们进一步比较了菱形网格上的紧致构象和非紧致构象。结果显示我们的模型和算法在菱形网格上预测氨基酸序列的蛋白质结构是有效的有意义的。     

miR-221对甲状腺乳头癌生物学特性的影响

目的:探讨miR-221对甲状腺乳头癌生物学特性的影响。方法:培养人甲状腺乳头癌细胞株BCPAP、K1、TPC-1和正常甲状腺细胞株Nthy-ori 3-1。将实验分为四组:A:miR-221模拟物组;B组:miR-221抑制物组;C:无关序列组;D:空白对照组。RT-q PCR的方法检测miR-221在各个细胞中的表达以及转染后各组细胞的表达;MTT实验检测转染后各组细胞的增殖;划痕实验检测转染后各组细胞的迁移能力;流式细胞仪检测转染后各组细胞的凋亡情况。结果:RT-qPCR检测miR-221在三个细胞株的表达情况显示,miR-221甲状腺乳头癌细胞株TPC-1的表达最高,因此选择TPC-1作为后续的研究;miR-221在转染后各组细胞的表达量显示,转染miR221模拟物的miR221的表达显著高于空白对照组,转染miR221抑制物的miR221的表达显著低于空白对照组(P0.001);MTT实验结果显示,转染miR-221模拟物组细胞的增殖速度最快,转染miR-221抑制物组细胞的增殖速度最慢,miR-221模拟物组和miR-221抑制物组细胞从第三天开始与空白对照组有显著差异(P0.01),无关对照组与空白对照组无显著差异(P0.05);划痕实验结果显示,转染miR-221模拟物组细胞的迁移数显著高于空白对照组,转染miR-221抑制物组细胞的迁移数显著低于空白对照组(P0.01),无关对照组与空白对照组无显著差异(P0.05);流式细胞仪结果显示,转染miR-221模拟物组细胞凋亡率显著低于空白对照组(P0.01),转染miR-221抑制组细胞凋亡率显著高于空白对照组(P0.001),转染无关对照对细胞凋亡无影响(P0.05)。结论:过表达miR-221可促进细胞增殖、迁移,抑制细胞凋亡。抑制miR-221表达可降低细胞增殖、迁移,增加细胞凋亡。     

miR-218与口腔癌顺铂耐药性的相关性分析

本研究检测了顺铂敏感性和非敏感性口腔癌组织中的miR-218表达,发现在非敏感性口腔癌中miR-218的表达水平显著增加。本研究将人舌鳞状细胞癌细胞系(UM1)暴露在顺铂中6个月,发现miR-218在顺铂耐药的UM1细胞中明显上调。通过转染miR-218抑制剂可显著增加UM1细胞对顺铂的敏感性。转染miR-218模拟物可抑制PPP2R5A的表达。转染过表达PPP2R5A的慢病毒可增加UM1细胞对顺铂的敏感性。转染miR-218模拟物增强了UM1细胞活力,而转染过表达PPP2R5A的慢病毒则抑制了miR-218诱导的细胞活力。转染miR-218模拟物上调了β-catenin的表达,而转染过表达PPP2R5A的慢病毒则抑制了β-catenin的上调。本研究证明miR-218是口腔癌中顺铂耐药性的重要调节因子。miR-218的上调通过抑制PPP2R5A,从而激活Wnt信号通路,进而降低了口腔癌的顺铂敏感性。     

An evolutionary strategy for all-atom folding of the 60-amino-acid bacterial ribosomal protein l20

We have investigated an evolutionary algorithm for de novo all-atom folding of the bacterial ribosomal protein L20. We report results of two simulations that converge to near-native conformations of this 60-amino-acid, four-helix protein. We observe a steady increase of "native content" in both simulated ensembles and a large number of near-native conformations in their final populations. We argue that these structures represent a significant fraction of the low-energy metastable conformations, which characterize the folding funnel of this protein. These data validate our all-atom free-energy force field PFF01 for tertiary structure prediction of a previously inaccessible structural family of proteins. We also compare folding simulations of the evolutionary algorithm with the basin-hopping technique for the Trp-cage protein. We find that the evolutionary algorithm generates a dynamic memory in the simulated population, which leads to faster overall convergence.     

Protein folding on the hexagonal lattice in the HP model

In this paper, we introduce the 2D hexagonal lattice as a biologically meaningful alternative to the standard square lattice for the study of protein folding in the HP model. We show that the hexagonal lattice alleviates the "sharp turn" problem and models certain aspects of the protein secondary structure more realistically. We present a 1/6-approximation and a clustering heuristic for protein folding on the hexagonal lattice. In addition to these two algorithms, we also implement a Monte Carlo Metropolis algorithm and a branch-and-bound partial enumeration algorithm, and conduct experiments to compare their effectiveness.     

Practicality and time complexity of a sparsified RNA folding algorithm

Commonly used RNA folding programs compute the minimum free energy structure of a sequence under the pseudoknot exclusion constraint. They are based on Zuker's algorithm which runs in time O(n(3)). Recently, it has been claimed that RNA folding can be achieved in average time O(n(2)) using a sparsification technique. A proof of quadratic time complexity was based on the assumption that computational RNA folding obeys the "polymer-zeta property". Several variants of sparse RNA folding algorithms were later developed. Here, we present our own version, which is readily applicable to existing RNA folding programs, as it is extremely simple and does not require any new data structure. We applied it to the widely used Vienna RNAfold program, to create sibRNAfold, the first public sparsified version of a standard RNA folding program. To gain a better understanding of the time complexity of sparsified RNA folding in general, we carried out a thorough run time analysis with synthetic random sequences, both in the context of energy minimization and base pairing maximization. Contrary to previous claims, the asymptotic time complexity of a sparsified RNA folding algorithm using standard energy parameters remains O(n(3)) under a wide variety of conditions. Consistent with our run-time analysis, we found that RNA folding does not obey the "polymer-zeta property" as claimed previously. Yet, a basic version of a sparsified RNA folding algorithm provides 15- to 50-fold speed gain. Surprisingly, the same sparsification technique has a different effect when applied to base pairing optimization. There, its asymptotic running time complexity appears to be either quadratic or cubic depending on the base composition. The code used in this work is available at: .     

Routes are trees: the parsing perspective on protein folding

An important puzzle in structural biology is the question of how proteins are able to fold so quickly into their unique native structures. There is much evidence that protein folding is hierarchic. In that case, folding routes are not linear, but have a tree structure. Trees are commonly used to represent the grammatical structure of natural language sentences, and chart parsing algorithms efficiently search the space of all possible trees for a given input string. Here we show that one such method, the CKY algorithm, can be useful both for providing novel insight into the physical protein folding process, and for computational protein structure prediction. As proof of concept, we apply this algorithm to the HP lattice model of proteins. Our algorithm identifies all direct folding route trees to the native state and allows us to construct a simple model of the folding process. Despite its simplicity, our model provides an account for the fact that folding rates depend only on the topology of the native state but not on sequence composition.     

The nature of folded states of globular proteins.

We suggest, using dynamical simulations of a simple heteropolymer modelling the alpha-carbon sequence in a protein, that generically the folded states of globular proteins correspond to statistically well-defined metastable states. This hypothesis, called the metastability hypothesis, states that there are several free energy minima separated by barriers of various heights such that the folded conformations of a polypeptide chain in each of the minima have similar structural characteristics but have different energies from one another. The calculated structural characteristics, such as bond angle and dihedral angle distribution functions, are assumed to arise from only those configurations belonging to a given minimum. The validity of this hypothesis is illustrated by simulations of a continuum model of a heteropolymer whose low temperature state is a well-defined beta-barrel structure. The simulations were done using a molecular dynamics algorithm (referred to as the "noisy" molecular dynamics method) containing both friction and noise terms. It is shown that for this model there are several distinct metastable minima in which the structural features are similar. Several new methods of analyzing fluctuations in structures belonging to two distinct minima are introduced. The most notable one is a dynamic measure of compactness that can in principle provide the time required for maximal compactness to be achieved. The analysis shows that for a given metastable state in which the protein has a well-defined folded structure the transition to a state of higher compactness occurs very slowly, lending credence to the notion that the system encounters a late barrier in the process of folding to the most compact structure. The examination of the fluctuations in the structures near the unfolding----folding transition temperature indicates that the transition state for the unfolding to folding process occurs closer to the folded state.     

一种预测单链RNA分子二级结构的计算机算法

本文给出了一个利用已知能量数据构成具有最小自由能的单链RNA分子二级结构的计算机算法,并给出了此算法的可行性证明和应用实例。     

Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints

Background  

We are interested in the problem of predicting secondary structure for small sets of homologous RNAs, by incorporating limited comparative sequence information into an RNA folding model. The Sankoff algorithm for simultaneous RNA folding and alignment is a basis for approaches to this problem. There are two open problems in applying a Sankoff algorithm: development of a good unified scoring system for alignment and folding and development of practical heuristics for dealing with the computational complexity of the algorithm.     

Protein folding: Optimized sequences obtained by simulated breeding in a minimalist model

For a minimalist model of protein folding, which we introduced recently, we investigate various methods to obtain folding sequences. A detailed study of random sequences shows that, for this model, such sequences usually do not fold to their ground states during simulations. Straightforward techniques for the construction of folding sequences, based solely on the target structure, fail. We describe in detail an optimization algorithm, based on genetic algorithms, for the “simulated breeding” of folding sequences in this model. We find that, for any target structure studied, there is not only a single folding sequence but a patch of sequences in sequence space that fold to this structure. In addition, we show that, much as in real proteins, nonhomologous sequences may fold to the same target structure. © 1997 John Wiley & Sons, Inc.     

Gatekeepers in the ribosomal protein s6: thermodynamics, kinetics, and folding pathways revealed by a minimalist protein model

We investigate the effect of structural gatekeepers on the folding of the ribosomal protein S6. Folding thermodynamics and early refolding kinetics are studied for this system utilizing computer simulations of a minimalist protein model. When gatekeepers are eliminated, the thermodynamic signature of a folding intermediate emerges, and a marked decrease in folding efficiency is observed. We explain the prerequisites that determine the "strength" of a given gatekeeper. The investigated gatekeepers are found to have distinct functions, and to guide the folding and time-dependent packing of non-overlapping secondary structure elements in the protein. Gatekeepers avoid kinetic traps during folding by favoring the formation of "productive topologies" on the way to the native state. The trends in folding rates in the presence/absence of gatekeepers observed for our minimalist model of S6 are in very good agreement with experimental data on this protein.