一种快速非比对的蛋白质序列相似性与进化分析方法

本文提出了一种新的快速非比对的蛋白质序列相似性与进化分析方法。在刻画蛋白质序列特征时,首先将氨基酸的10种理化性质通过主成分分析浓缩为6个主成分,并且将每条蛋白质序列里的氨基酸数目作为权重对主成分得分值进行加权平均,然后再融合氨基酸的位置信息构成一个26维的蛋白质序列特征向量,最后利用欧式距离度量蛋白质序列间的相似性及进化关系。通过对3个蛋白质序列数据集的测试表明,本文提出的方法能将每条蛋白质序列准确聚类,并且简便快捷,说明了该方法的有效性。     

基于氨基酸特征序列的蛋白质结构分析

针对蛋白质序列中氨基酸的核苷酸组成部分及其相关特征信息,提出另外的σ-等序列的概念,并讨论了其主要特征与次要特征,可作为对蛋白质进行定性和定量比较的一种方法,用来判断这些物种的同源性和相似性程度。然后,对所取的全α螺旋,全β折叠和αβ类序列,利用σ-,τ-,στ序列的概念,给出蛋白质序列的相关氨基酸特征序列。同时对三类共18个蛋白质序列进行数值刻划,给出数值刻划图并进行分析。     

DNA序列信息的一种新的测度

根据信息理论给出了测度ＤＮＡ序列信息的一种新的方法,获得ＤＮＡ序列４个层次的信息量测度：Ｉｂ,Ｉｆ（１）,Ｉｆ（２）ａｎｄＩｆ（３）,这４种信息测度可分别用来测度ＤＮＡ的碱基序列、密码子序列、编码蛋白质序列和功能蛋白质序列的信息量。从Ｍ．ｅｄｕｌｉｓ的线粒体基因组中两个较短的编码蛋白质的ＤＮＡ序列和使用具有不同倍性的间并密码子组组成的模拟ＤＮＡ序列中所获得计算结果表明,这些信息测度确实能用来揭示所     

大熊猫LSM3c DNA序列的克隆及序列分析

运用RT-PCR技术首次从大熊猫Ailuropoda melanoleuca的肌肉组织总RNA中成功克隆了LSM3的表达序列,并对其进行了测序及初步分析.结果 表明:大熊猫LSM3基因的表达序列含有一个完整的开放阅读框,长度为306 bp,编码102个氨基酸的蛋白质,分子量为11.845 kDa,pI为4.58,含有1个蛋白激酶C磷酸化位点、4个酪蛋白激酶Ⅱ磷酸化位点、1个酪氨酸激酶磷酸化位点和1个细胞附着序列.进一步分析发现,大熊猫LSM3基因的表达序列与已报道的部分哺乳动物具有很高的相似性,其编码的氨基酸序列与其他哺乳动物完全一致.     

外显子和内含子的序列复杂性

引入了两个新的关于序列复杂性的测度,并以此为指标分析比较了结构基因序列中的外显子和内含子的复杂性差异。     

一种用于蛋白质相似性分析的新的相对距离

本文论述了一种新的相对距离,用于分析不同蛋白质序列的相似性分析和构造进化树．此种距离基于Lempel-Zip复杂度,不需要进行序列比对和复杂性算法．为了说明这种距离的合理性,本文对8个物种进行了相似性分析并构造了其进化树．     

SARS冠状病毒全基因组序列初步分析

对已经完成全序列测定的12个SARS病毒基因组进行了多序列比对,发现序列主体部分29708 b具有99．82％的相同碱基,除2个序列各有5个和6个碱基的缺失外,其余部分共有42个位点核苷酸碱基的差异,其中28个位点的碱基差异可引起氨基酸残基改变。利用蛋白质二级结构和跨膜螺旋预测以及蛋白质定位等生物信息学工具,分析了这些产生氨基酸改变部位的蛋白质构像,推测了可能产生的结构和功能改变,为进一步生物学实验提供参考。所有分析结果同时在北京大学生物信息中心抗SARS网站(antisars.cbi.pku．edu．cn)上发布。     

生物序列比对算法的研究现状

序列比对是生物信息学研究的一个重要工具,它在序列拼接、蛋白质结构预测、蛋白质结构功能分析、系统进化分析、数据库检索以及引物设计等问题的研究中被广泛使用。本文详细介绍了在生物信息学中常用的一些序列比对算法,比较了这些算法所需的计算复杂度,优缺点,讨论了各自的使用范围,并指出今后序列比对研究的发展方向。     

氨基酸残基归类及用简化后的字符识别蛋白质结构保守区域

序列比对是寻找蛋白质结构保守性区域的常用方法, 然而当序列相似小于30%时比对准确度却不高, 这是因为在这些序列中具有相似结构功能的不同残基在序列比对中往往被错误配对. 基于相似的物理化学性质, 某些残基可以被归类为一组, 而应用这些简化后的残基字符可以有效地简化蛋白质序列的复杂性并保持序列的主要信息. 因此, 如果20种天然氨基酸残基能够正确的归类, 可以有效地提高序列比对的准确度. 本文基于蛋白质结构比对数据库DAPS, 提出了一种新的氨基酸残基归类方法, 并可以同时得到不同简化程度下的替代矩阵用于序列比对. 归类的合理性由相互熵方法确认, 并且应用简化后的字符表于序列比对来识别蛋白质的结构保守区域. 结果表明, 当氨基酸残基字符简化到9个左右时能够有效地提高序列比对的准确度.     

一个新的多序列比对算法

多序列比对是生物信息学中基础而又重要的序列分析方法.本文提出一种新的多序列比对算法,该算法综合了渐进比对方法和迭代策略,采用加权函数以调整序列的有偏分布,用neighbor-joining方法构建指导树以确定渐进比对的顺序.通过对BAlibASE中142组蛋白质序列比对的测试,验证了本算法的有效性.与Multalin算法比较的结果表明,本算法能有效地提高分歧较大序列的比对准确率.     

Two Dimensional Yau-Hausdorff Distance with Applications on Comparison of DNA and Protein Sequences

Comparing DNA or protein sequences plays an important role in the functional analysis of genomes. Despite many methods available for sequences comparison, few methods retain the information content of sequences. We propose a new approach, the Yau-Hausdorff method, which considers all translations and rotations when seeking the best match of graphical curves of DNA or protein sequences. The complexity of this method is lower than that of any other two dimensional minimum Hausdorff algorithm. The Yau-Hausdorff method can be used for measuring the similarity of DNA sequences based on two important tools: the Yau-Hausdorff distance and graphical representation of DNA sequences. The graphical representations of DNA sequences conserve all sequence information and the Yau-Hausdorff distance is mathematically proved as a true metric. Therefore, the proposed distance can preciously measure the similarity of DNA sequences. The phylogenetic analyses of DNA sequences by the Yau-Hausdorff distance show the accuracy and stability of our approach in similarity comparison of DNA or protein sequences. This study demonstrates that Yau-Hausdorff distance is a natural metric for DNA and protein sequences with high level of stability. The approach can be also applied to similarity analysis of protein sequences by graphic representations, as well as general two dimensional shape matching.     

Alignment-free comparison of genome sequences by a new numerical characterization

In order to compare different genome sequences, an alignment-free method has proposed. First, we presented a new graphical representation of DNA sequences without degeneracy, which is conducive to intuitive comparison of sequences. Then, a new numerical characterization based on the representation was introduced to quantitatively depict the intrinsic nature of genome sequences, and considered as a 10-dimensional vector in the mathematical space. Alignment-free comparison of sequences was performed by computing the distances between vectors of the corresponding numerical characterizations, which define the evolutionary relationship. Two data sets of DNA sequences were constructed to assess the performance on sequence comparison. The results illustrate well validity of the method. The new numerical characterization provides a powerful tool for genome comparison.     

Grouping of amino acids and recognition of protein structurally conserved regions by reduced alphabets of amino acids

Sequence alignment is a common method for finding protein structurally conserved/similar regions. However, sequence alignment is often not accurate if sequence identities between to-be-aligned sequences are less than 30%. This is because that for these sequences, different residues may play similar structural roles and they are incorrectly aligned during the sequence alignment using substitution matrix consisting of 20 types of residues. Based on the similarity of physicochemical features, residues can be clustered into a few groups. Using such simplified alphabets, the complexity of protein sequences is reduced and at the same time the key information encoded in the sequences remains. As a result, the accuracy of sequence alignment might be improved if the residues are properly clustered. Here, by using a database of aligned protein structures (DAPS), a new clustering method based on the substitution scores is proposed for the grouping of residues, and substitution matrices of residues at different levels of simplification are constructed. The validity of the reduced alphabets is confirmed by relative entropy analysis. The reduced alphabets are applied to recognition of protein structurally conserved/similar regions by sequence alignment. The results indicate that the accuracy or efficiency of sequence alignment can be improved with the optimal reduced alphabet with N around 9.     

Grouping of amino acids and recognition of protein structurally conserved regions by reduced alphabets of amino acids

Sequence alignment is a common method for finding protein structurally conserved/similar regions. However, sequence alignment is often not accurate if sequence identities between to-be-aligned sequences are less than 30%. This is because that for these sequences, different residues may play similar structural roles and they are incorrectly aligned during the sequence alignment using substitution matrix consisting of 20 types of residues. Based on the similarity of physicochemical features, residues can be clustered into a few groups. Using such simplified alphabets, the complexity of protein sequences is reduced and at the same time the key information encoded in the sequences remains. As a result, the accuracy of sequence alignment might be improved if the residues are properly clustered. Here, by using a database of aligned protein structures (DAPS), a new clustering method based on the substitution scores is proposed for the grouping of residues, and substitution matrices of residues at different levels of simplification are constructed. The validity of the reduced alphabets is confirmed by relative entropy analysis. The reduced alphabets are applied to recognition of protein structurally conserved/similar regions by sequence alignment. The results indicate that the accuracy or efficiency of sequence alignment can be improved with the optimal reduced alphabet with N around 9. Supported by the National Natural Science Foundation of China (Grant Nos. 90403120, 10474041 and 10021001) and the Nonlinear Project (973) of the NSM     

A probabilistic measure for alignment-free sequence comparison

MOTIVATION: Alignment-free sequence comparison methods are still in the early stages of development compared to those of alignment-based sequence analysis. In this paper, we introduce a probabilistic measure of similarity between two biological sequences without alignment. The method is based on the concept of comparing the similarity/dissimilarity between two constructed Markov models. RESULTS: The method was tested against six DNA sequences, which are the thrA, thrB and thrC genes of the threonine operons from Escherichia coli K-12 and from Shigella flexneri; and one random sequence having the same base composition as thrA from E.coli. These results were compared with those obtained from CLUSTAL W algorithm (alignment-based) and the chaos game representation (alignment-free). The method was further tested against a more complex set of 40 DNA sequences and compared with other existing sequence similarity measures (alignment-free). AVAILABILITY: All datasets and computer codes written in MATLAB are available upon request from the first author.     

Sequence Complexity Effects on Speech Production in Healthy Speakers and Speakers with Hypokinetic or Ataxic Dysarthria

The present study investigated the effects of sequence complexity, defined in terms of phonemic similarity and phonotoactic probability, on the timing and accuracy of serial ordering for speech production in healthy speakers and speakers with either hypokinetic or ataxic dysarthria. Sequences were comprised of strings of consonant-vowel (CV) syllables with each syllable containing the same vowel, /a/, paired with a different consonant. High complexity sequences contained phonemically similar consonants, and sounds and syllables that had low phonotactic probabilities; low complexity sequences contained phonemically dissimilar consonants and high probability sounds and syllables. Sequence complexity effects were evaluated by analyzing speech error rates and within-syllable vowel and pause durations. This analysis revealed that speech error rates were significantly higher and speech duration measures were significantly longer during production of high complexity sequences than during production of low complexity sequences. Although speakers with dysarthria produced longer overall speech durations than healthy speakers, the effects of sequence complexity on error rates and speech durations were comparable across all groups. These findings indicate that the duration and accuracy of processes for selecting items in a speech sequence is influenced by their phonemic similarity and/or phonotactic probability. Moreover, this robust complexity effect is present even in speakers with damage to subcortical circuits involved in serial control for speech.     

大豆Kunitz型胰蛋白酶抑制剂新类型Tid的全序列分析

大豆ｋｕｎｉｔｚ型胰蛋白酶抑制剂（ＳＢＴｉＡ２）是一种大量存在于大豆（Ｇｌｙｃｉｎｅｍａｘ）中的种子贮藏蛋白．虽然对它的生化特性及结构已有较多的研究,但它在体内的主要功能仍不很清楚．国际上所发现的３个由显性等位基因Ｔｉａ、Ｔｉｂ、Ｔｉｃ编码的大豆ｋｕｎｉｔｚ胰蛋白酶抑制剂的氨基酸顺序已被明确测定,相互间有一到多个氨基酸残基的不同［１］．Ｔｉｄ是从我国１５０００余份大豆资源中筛选到的唯一一份ｋｕｎｉｔｚ型胰蛋白酶抑制剂位点的新类型,遗传分析证明它是另一个ＳＢＴｉＡ２的显性等位基因［２,３］．严…     

Sequence, structure and energetic determinants of phosphopeptide selectivity of SH2 domains

Here, we present an approach for the prediction of binding preferences of members of a large protein family for which structural information for a number of family members bound to a substrate is available. The approach involves a number of steps. First, an accurate multiple alignment of sequences of all members of a protein family is constructed on the basis of a multiple structural superposition of family members with known structure. Second, the methods of continuum electrostatics are used to characterize the energetic contribution of each residue in a protein to the binding of its substrate. Residues that make a significant contribution are mapped onto the protein sequence and are used to define a "binding site signature" for the complex being considered. Third, sequences whose structures have not been determined are checked to see if they have binding-site signatures similar to one of the known complexes. Predictions of binding affinity to a given substrate are based on similarities in binding-site signature. An important component of the approach is the introduction of a context-specific substitution matrix suitable for comparison of binding-site residues.The methods are applied to the prediction of phosphopeptide selectivity of SH2 domains. To this end, the energetic roles of all protein residues in 17 different complexes of SH2 domains with their cognate targets are analyzed. The total number of residues that make significant contributions to binding is found to vary from nine to 19 in different complexes. These energetically important residues are found to contribute to binding through a variety of mechanisms, involving both electrostatic and hydrophobic interactions. Binding-site signatures are found to involve residues in different positions in SH2 sequences, some of them as far as 9A away from a bound peptide. Surprisingly, similarities in the signatures of different domains do not correlate with whole-domain sequence identities unless the latter is greater than 50%.An extensive comparison with the optimal binding motifs determined by peptide library experiments, as well as other experimental data indicate that the similarity in binding preferences of different SH2 domains can be deduced on the basis of their binding-site signatures. The analysis provides a rationale for the empirically derived classification of SH2 domains described by Songyang & Cantley, in that proteins in the same group are found to have similar residues at positions important for binding. Confident predictions of binding preference can be made for about 85% of SH2 domain sequences found in SWISSPROT. The approach described in this work is quite general and can, in principle, be used to analyze binding preferences of members of large protein families for which structural information for a number of family members is available. It also offers a strategy for predicting cross-reactivity of compounds designed to bind to a particular target, for example in structure-based drug design.     

Sequence complexity profiles of prokaryotic genomic sequences: a fast algorithm for calculating linguistic complexity

MOTIVATION: One of the major features of genomic DNA sequences, distinguishing them from texts in most spoken or artificial languages, is their high repetitiveness. Variation in the repetitiveness of genomic texts reflects the presence and density of different biologically important messages. Thus, deviation from an expected number of repeats in both directions indicates a possible presence of a biological signal. Linguistic complexity corresponds to repetitiveness of a genomic text, and potential regulatory sites may be discovered through construction of typical patterns of complexity distribution. RESULTS: We developed software for fast calculation of linguistic sequence complexity of DNA sequences. Our program utilizes suffix trees to compute the number of subwords present in genomic sequences, thereby allowing calculation of linguistic complexity in time linear in genome size. The measure of linguistic complexity was applied to the complete genome of Haemophilus influenzae. Maps of complexity along the entire genome were obtained using sliding windows of 40, 100, and 2000 nucleotides. This approach provided an efficient way to detect simple sequence repeats in this genome. In addition, local profiles of complexity distribution around the starts of translation were constructed for 21 complete prokaryotic genomes. We hypothesize that complexity profiles correspond to evolutionary relationships between organisms. We found principal differences in profiles of the GC-rich and other (non-GC-rich) genomes. We also found characteristic differences in profiles of AT genomes, which probably reflect individual species variations in translational regulation. AVAILABILITY: The program is available upon request from Alexander Bolshoy or at http://csweb.haifa.ac.il/library/#complex.     

Sequence organization of the soybean genome

The total complexity of one constituent soybean (Glycine max) genome is estimated to be 1.29 . 10(9) nucleotide pairs, as determined by analysis of the reassociation kinetics of sheared (0.47 kilobase) DNA. Single copy sequences are estimated to represent from 53 to 64% of the genome by analysis of hydroxyapatite binding of repetitive DNA as a function of fragment length. From 65 to 70% of these single copy sequences have a short period interspersion with 1.11--1.36 kilobase lengths alternating with 0.3--0.4 kilobase repetitive sequence elements. The repetitive sequences of soybean DNA are interspersed both among themselves and among single copy regions of the genome.