p53蛋白质C端的三维结构及生物功能区

利用p53 C端118个氨基酸的mRNA二级结构和Chou-Fasman蛋白质二级结构预测原则,预测p53蛋白质C端289～325为卷曲肽段,368～393段包括两段螺旋结构: α₁ 368～373, α₂ 381～388.其中三段已知的蛋白质二级结构与此mRNA二级结构单元间有准确的对应关系.与四种以多重序列联配为基础的蛋白质二级结构预测方法（准确率均为73.20%左右）相对照,预测结果基本一致.结合单体聚合区31个氨基酸晶体结构,在SGI INDIGO²工作站上构建了p53 C端108个残基的三维结构.进一步揭示了p53 C端诸多生物功能区之间的空间构象关系.     

眼镜王蛇蛇毒神经毒素CM—11二级结构单元的判定

眼镜王蛇毒液抽提物ＣＭ－１１为含７２个残基的长链神经毒素,对其进行了ＤＱＦ－ＣＯＳＹ,ＴＯＣＳＹ和ＮＯＥＳＹ等一系列２Ｄ－ＮＭＲ谱测定,通过系统地分析各种ＮＯＥ信息,化学位移的分布等数据推测了蛋白质有规律二级结构,最后利用ＭＣＤ主链引导法确定它的二级结构,其中有三段反平行β折叠股（Ｉ２０～Ｗ２６,Ｒ３７～Ａ４３和Ｖ５３～Ｓ５９）,一段α螺旋构象（Ｗ３０～Ｇ３５）和四个可能的转角（Ｐ７～Ｋ１０,Ｃ１     

脯氨酸对蛋白质热稳定性的贡献

单一氨基酸的置换可以改变酶的热稳定性。脯氨酸（Ｐｒｏ）残基在蛋白质结构及其热稳定性中具有特殊作用。它十分偏爱β－转折或无规卷曲结构,而很少出现在α－螺旋和β－折叠中。分析认为在改善酶热稳定性的蛋白质工程中,只要主链构象不发生骤变,则可在适当的β－转折或无规卷曲中引入Ｐｒｏ,通过其刚性的吡咯烷环,降低蛋白质去折叠时的骨架熵,从面使其周围的构象更合理。这一Ｐｒｏ理论（ｔｈｅ ｐｒｏｌｉｎｅ ｔｈｅｏｒ     

α螺旋和β折叠连接短肽的构象分析──蛋白质超二级结构模块（MOTIF）研究（Ⅰ）

对２４０个分辨率在２５Ａ以上较高度蛋白质结构中α螺旋和β折叠的连接短肽进行了系统分析。着重研究了一个至五个残基长的短连接肽,依它们所连接的二级结构分成四种类型分析,即αααβ和ββ。对非规则结构区,作者采用了五种残基构象状态－ａ,ｂ,ｃ,ｌ,ｔ－,进行系统研究,识别出５０种发生频率在５次以上的非规则结构,其中出现次数多于２５次的有１１种类型。这１１种类型的连接多肽是较普遍发生的。此结果对揭示蛋白质非规则结构区的结构规律有一定意义为超二级结构结构模型和预测的进一步研究建立了基础。     

α螺旋和β折叠连接短肽的构象分析──蛋白质超二级结构模块（MOTIF）研究（Ⅰ）

对２４０个分辨率在２５Ａ以上较高度蛋白质结构中α螺旋和β折叠的连接短肽进行了系统分析。着重研究了一个至五个残基长的短连接肽,依它们所连接的二级结构分成四种类型分析,即αααβ和ββ。对非规则结构区,作者采用了五种残基构象状态－ａ,ｂ,ｃ,ｌ,ｔ－,进行系统研究,识别出５０种发生频率在５次以上的非规则结构,其中出现次数多于２５次的有１１种类型。这１１种类型的连接多肽是较普遍发生的。此结果对揭示蛋白质非规则结构区的结构规律有一定意义为超二级结构结构模型和预测的进一步研究建立了基础。     

用FT—IR技术研究人卵泡促性腺激素释放肽hF—GRP及其类似物TF14的二级结构

用付立叶变换红外（ＦＴ－ＩＲ）技术,定量分析了人卵泡促性腺激素释放肽ｈＦ－ＧＲＰ及类似物ＴＦ１４这两个多肽在重水溶液中的二级结构,结果为ｈＦ－ＧＲＰ有近两分之一的残基处于无规卷曲,其余部分是非典型的伸展结构,ＴＦ１４则基本上处于伸展和转角结构,无规和螺旋的成分很少,这与用二维核磁共振技术测定的ｈＦ－ＧＲＰ和ＴＦ１４的溶液构象实验结果非常吻合。     

不同亚型乙肝病毒Pre-S(2)蛋白二级结构及抗原表位的预测与比较

本文采用Chou和Fasman方法预测adw,adr,ayw三种亚型的乙肝病毒Pres(2)蛋白的二级结构;并用双亲性方案和亲水性方案分析了抗原表位。结果显示三者均可能含有较多的β片层和β转折;N-末端30个残基所形成的二级结构较保守,而C-末端顺序的构象在亚型间差别较大;Th细胞识别的表位可能在39—49肽段;B细胞识别的表位可能主要在12—18残基或其附近。     

天花粉蛋白小结构域N端TCS182—200同源片段的构象研究

以天花粉蛋白小结构域Ｎ端ＴＣＳ１８２－２００同源片段序列为基础,设计Ｔ１４,Ｔ１８和ＴＤＫ３个模型肽。本文分析了模型肽的肽链柔性和侧链两亲性,预测二级结构形成势,并通过多肽固相合成和圆二色性研究模型肽的溶液二级结构,比较理论预测和实测结果。在水溶液中,Ｔ１８为β－折叠,ＴＤＫ含有一定量α－螺旋;而Ｔ１４基本上为无规卷曲,但在碱性条件下有类似螺肇的亚稳结构存在。     

用人工神经网络方法预测蛋白质超二级结构

蛋白质超二级结构,即由α－螺旋和β－折叠等二级结构单元和连接短肽组成的超二级结构,是蛋白质结构研究中的一个重要层次。目前蛋白质超二级结构的预测工作尚属摸索阶段,还没有成熟的方法。人工神经网络预测方法是近年来在二级结构预测中发展起来的新方法。本文成功的将人工神经网络引入蛋白质超二级结构的预测工作中,结果表明蛋白质的超二级结构的发生与其局域的氨基酸的序列模式有重要联系,可以由蛋白质的一级结构序列预测该     

肽键的统计分析和蛋白质的二级结构

 本文对蛋白质序列的肽键进行了统计分析,计算了二肽构象参数P_α、P_β、P_c和三肽构象参数Q_α、Q_β、Q_c。在此基础上提出了由氨基酸序列预测二级结构的规则。预测的正确率达90％,优于Chou-Fasman方法。这个结果表明二肽(三肽)关联在形成蛋白质二级结构中具有明显的重要性。     

Contact patterns between helices and strands of sheet define protein folding patterns

Comparing and classifying protein folding patterns allows organizing the known structures and enumerating possible protein structural patterns including those not yet observed. We capture the essence of protein folding patterns in a concise tableau representation based on the order and contact patterns of secondary structures: helices and strands of sheet. The tableaux are intelligible to both humans and computers. They provide a database, derived from the Protein Data Bank, mineable in studies of protein architecture. Using this database, we have: (i) determined statistical properties of secondary structure contacts in an unbiased set of protein domains from ASTRAL, (ii) observed that in 98% of cases, the tableau is a faithful representation of the folding pattern as classified in SCOP, (iii) demonstrated that to a large extent the local structure of proteins indicates their complete folding topology, and (iv) studied the use of the representation for fold identification.     

Extended secondary structures in proteins

Supersecondary structures of proteins have been systematically searched and classified, but not enough attention has been devoted to such large edifices beyond the basic identification of secondary structures. The objective of the present study is to show that the association of secondary structures that share some of their backbone residues is a commonplace in globular proteins, and that such deeper fusion of secondary structures, namely extended secondary structures (ESSs), helps stabilize the original secondary structures and the resulting tertiary structures. For statistical purposes, a set of 163 proteins from the protein databank was randomly selected and a few specific cases are structurally analyzed and characterized in more detail. The results point that about 30% of the residues from each protein, on average, participate in ESS. Alternatively, for the specific cases considered, our results were based on the secondary structures produced after extensive Molecular Dynamics simulation of a protein–aqueous solvent system. Based on the very small width of the time distribution of the root mean squared deviations, between the ESS taken along the simulation and the ESS from the mean structure of the protein, for each ESS, we conclude that the ESSs significantly increase the conformational stability by forming very stable aggregates. The ubiquity and specificity of the ESS suggest that the role they play in the structure of proteins, including the domains formation, deserves to be thoroughly investigated.     

Protein loop structure prediction with flexible stem geometries

The structure prediction of loops with flexible stem residues is addressed in this article. While the secondary structure of the stem residues is assumed to be known, the geometry of the protein into which the loop must fit is considered to be unknown in our methodology. As a consequence, the compatibility of the loop with the remainder of the protein is not used as a criterion to reject loop decoys. The loop structure prediction with flexible stems is more difficult than fitting loops into a known protein structure in that a larger conformational space has to be covered. The main focus of the study is to assess the precision of loop structure prediction if no information on the protein geometry is available. The proposed approach is based on (1) dihedral angle sampling, (2) structure optimization by energy minimization with a physically based energy function, (3) clustering, and (4) a comparison of strategies for the selection of loops identified in (3). Steps (1) and (2) have similarities to previous approaches to loop structure prediction with fixed stems. Step (3) is based on a new iterative approach to clustering that is tailored for the loop structure prediction problem with flexible stems. In this new approach, clustering is not only used to identify conformers that are likely to be close to the native structure, but clustering is also employed to identify far-from-native decoys. By discarding these decoys iteratively, the overall quality of the ensemble and the loop structure prediction is improved. Step (4) provides a comparative study of criteria for loop selection based on energy, colony energy, cluster density, and a hybrid criterion introduced here. The proposed method is tested on a large set of 3215 loops from proteins in the Pdb-Select25 set and to 179 loops from proteins from the Casp6 experiment.     

蛋白质二级结构指定

蛋白质二级结构是指蛋白质骨架结构中有规律重复的构象。由蛋白质原子坐标正确地指定蛋白质二级结构是分析蛋白质结构与功能的基础,二级结构的指定对于蛋白质分类、蛋白质功能模体的发现以及理解蛋白质折叠机制有着重要的作用。并且蛋白质二级结构信息广泛应用到蛋白质分子可视化、蛋白质比对以及蛋白质结构预测中。目前有超过20种蛋白质二级结构指定方法,这些方法大体可以分为两大类:基于氢键和基于几何,不同方法指定结果之间的差异较大。由于尚没有蛋白质二级结构指定方法的综述文献,因此,本文主要介绍和总结已有蛋白质二级结构指定方法。     

Structure alignment via Delaunay tetrahedralization

A novel protein structure alignment technique has been developed reducing much of the secondary and tertiary structure to a sequential representation greatly accelerating many structural computations, including alignment. Constructed from incidence relations in the Delaunay tetrahedralization, alignments of the sequential representation describe structural similarities that cannot be expressed with rigid-body superposition and complement existing techniques minimizing root-mean-squared distance through superposition. Restricting to the largest substructure superimposable by a single rigid-body transformation determines an alignment suitable for root-mean-squared distance comparisons and visualization. Restricted alignments of a test set of histones and histone-like proteins determined superpositions nearly identical to those produced by the established structure alignment routines of DaliLite and ProSup. Alignment of three, increasingly complex proteins: ferredoxin, cytidine deaminase, and carbamoyl phosphate synthetase, to themselves, demonstrated previously identified regions of self-similarity. All-against-all similarity index comparisons performed on a test set of 45 class I and class II aminoacyl-tRNA synthetases closely reproduced the results of established distance matrix methods while requiring 1/16 the time. Principal component analysis of pairwise tetrahedral decomposition similarity of 2300 molecular dynamics snapshots of tryptophanyl-tRNA synthetase revealed discrete microstates within the trajectory consistent with experimental results. The method produces results with sufficient efficiency for large-scale multiple structure alignment and is well suited to genomic and evolutionary investigations where no geometric model of similarity is known a priori.     

Sequence-similar, structure-dissimilar protein pairs in the PDB

It is often assumed that in the Protein Data Bank (PDB), two proteins with similar sequences will also have similar structures. Accordingly, it has proved useful to develop subsets of the PDB from which "redundant" structures have been removed, based on a sequence-based criterion for similarity. Similarly, when predicting protein structure using homology modeling, if a template structure for modeling a target sequence is selected by sequence alone, this implicitly assumes that all sequence-similar templates are equivalent. Here, we show that this assumption is often not correct and that standard approaches to create subsets of the PDB can lead to the loss of structurally and functionally important information. We have carried out sequence-based structural superpositions and geometry-based structural alignments of a large number of protein pairs to determine the extent to which sequence similarity ensures structural similarity. We find many examples where two proteins that are similar in sequence have structures that differ significantly from one another. The source of the structural differences usually has a functional basis. The number of such proteins pairs that are identified and the magnitude of the dissimilarity depend on the approach that is used to calculate the differences; in particular sequence-based structure superpositioning will identify a larger number of structurally dissimilar pairs than geometry-based structural alignments. When two sequences can be aligned in a statistically meaningful way, sequence-based structural superpositioning provides a meaningful measure of structural differences. This approach and geometry-based structure alignments reveal somewhat different information and one or the other might be preferable in a given application. Our results suggest that in some cases, notably homology modeling, the common use of nonredundant datasets, culled from the PDB based on sequence, may mask important structural and functional information. We have established a data base of sequence-similar, structurally dissimilar protein pairs that will help address this problem (http://luna.bioc.columbia.edu/rachel/seqsimstrdiff.htm).     

Definition of a New Information-Based Per-Residue Quality Parameter

For biomolecular NMR structures typically only a poor correspondence is observed between statistics derived from the experimental input data and structural quality indicators obtained from the structure ensembles. Here, we investigate the relationship between the amount of available NMR data and structure quality. By generating datasets with a predetermined information content and evaluating the quality of the resulting structure ensembles we show that there is, in contrast to previous findings, a linear relation between the information contained in experimental data and structural quality. From this relation, a new quality parameter is derived that provides direct insight, on a per-residue basis, into the extent to which structural quality is governed by the experimental input data.     

Using multiple templates to improve quality of homology models in automated homology modeling

When researchers build high-quality models of protein structure from sequence homology, it is today common to use several alternative target-template alignments. Several methods can, at least in theory, utilize information from multiple templates, and many examples of improved model quality have been reported. However, to our knowledge, thus far no study has shown that automatic inclusion of multiple alignments is guaranteed to improve models without artifacts. Here, we have carried out a systematic investigation of the potential of multiple templates to improving homology model quality. We have used test sets consisting of targets from both recent CASP experiments and a larger reference set. In addition to Modeller and Nest, a new method (Pfrag) for multiple template-based modeling is used, based on the segment-matching algorithm from Levitt's SegMod program. Our results show that all programs can produce multi-template models better than any of the single-template models, but a large part of the improvement is simply due to extension of the models. Most of the remaining improved cases were produced by Modeller. The most important factor is the existence of high-quality single-sequence input alignments. Because of the existence of models that are worse than any of the top single-template models, the average model quality does not improve significantly. However, by ranking models with a model quality assessment program such as ProQ, the average quality is improved by approximately 5% in the CASP7 test set.     

X-ray structure of Glu 53 human lysozyme.

The three-dimensional structure of a modified human lysozyme (HL), Glu 53 HL, in which Asp 53 was replaced by Glu, has been determined at 1.77 A resolution by X-ray analysis. The backbone structure of Glu 53 HL is essentially the same as the structure of wild-type HL. The root mean square difference for the superposition of equivalent C alpha atoms is 0.141 A. Except for the Glu 53 residue, the structure of the active site region is largely conserved between Glu 53 HL and wild-type HL. However, the hydrogen bond network differs because of the small shift or rotation of side chain groups. The carboxyl group of Glu 53 points to the carboxyl group of Glu 35 with a distance of 4.7 A between the nearest carboxyl oxygen atoms. A water molecule links these carboxyl groups by a hydrogen bond bridge. The active site structure explains well the fact that the binding ability for substrates does not significantly differ between Glu 53 HL and wild-type HL. On the other hand, the positional and orientational change of the carboxyl group of the residue 53 caused by the mutation is considered to be responsible for the low catalytic activity (ca. 1%) of Glu 53 HL. The requirement of precise positioning for the carboxyl group suggests the possibility that the Glu 53 residue contributes more than a simple electrostatic stabilization of the intermediate in the catalysis reaction.