基于序列疏水值震荡的折叠速率预测

蛋白质折叠速率的正确预测对理解蛋白质的折叠机理非常重要。本文从伪氨基酸组成的方法出发,提出利用序列疏水值震荡的方法来提取蛋白质氨基酸的序列顺序信息,建立线性回归模型进行折叠速率预测。该方法不需要蛋白质的任何二级结构、三级结构信息或结构类信息,可直接从序列对蛋白质折叠速率进行预测。对含有62个蛋白质的数据集,经过Jack．knife交互检验验证,相关系数达到0．804,表示折叠速率预测值与实验值有很好的相关性,说明了氨基酸序列信息对蛋白质折叠速率影响重要。同其他方法相比,本文的方法具有计算简单,输入参数少等特点。     

肽链的折叠方式不是蛋白质多样性的直接原因

从蛋白质的分子结构、翻译后的蛋白质质量控制、蛋白质结构预测方法 3个方面阐述肽链的折叠方式不是引起蛋白质结构和功能多样性的直接原因:在氨基酸序列确定的情况下,肽链的折叠方式是保守的;肽链一旦折叠错误,蛋白质质量控制系统会对其进行纠正或降解清除,若质量控制失败,错误折叠的蛋白质便会引起疾病;从氨基酸序列出发利用分子力学模拟方法和建模软件预测蛋白质三维构象的研究技术侧面印证了氨基酸序列确定的肽链其折叠方式具有保守性。     

聚α—氨基酸纤维的研究

<正> 在制造具有动物纤维相似性质的合成纤维时,应当引入蛋白质结构的慨念。丝是一种富含β-折叠结构的多肽,而羊毛则富有α-螺旋结构。当α-氨基酸聚合成聚α-氨基酸时,其一级结构与蛋白质一样为多肽,但其二级结构则可为α-螺旋、β-折叠或无规线圈,如果一种聚α-氨基酸纺成富含β-折叠     

蛋白质表面氨基酸特性研究进展

分布在蛋白质分子表面的暴露于溶剂的氨基酸所具有的一些特性对蛋白质的折叠和聚合过程、蛋白质一蛋白质相互作用以及蛋白质的功能具有重要影响。本文分析了蛋白质表面氨基酸在疏水性、保守性、静电势及结构方面的一些特性,阐述了近年来国际上利用这些特性对蛋白质一蛋白质相互作用界面进行预测的方法,最后介绍了几款预测蛋白质表面氨基酸的软件。     

蛋白质的氧化重折叠

经过近几十年来广泛而深入的研究,蛋白质氧化重折叠的机制已得到相当详细的阐明。1在已研究过的蛋白质中,大多数蛋白质都是沿着多途径而非单一、特定的途径进行氧化重折叠,这与折叠能量景观学说是一致的。2正是氨基酸残基间的天然相互作用而不是非天然的相互作用控制蛋白质的折叠过程。这一结论与含非天然二硫键的折叠中间体在牛胰蛋白酶抑制剂（BPTI）折叠中所起的重要作用并非相互排斥,因为后者仅仅是进行链内二硫键重排的化学反应所必需,与控制肽链折叠无直接关系。3根据对BPTI的研究,二硫键曾被认为仅仅具有稳定蛋白质天然结构的作用,既不决定折叠途径也不决定其三维构象。这一观点不适用于其它蛋白质。对凝乳酶原的研究表明,天然二硫键的形成是恢复天然构象的前提。天然二硫键的形成与肽键的正确折叠相辅相成,更具有普遍意义。4在氧化重折叠的早期,二硫键的形成基本上是一个随机过程,随着肽链的折叠二硫键的形成越来越受折叠中间体构象的限制。提高重组蛋白质的复性产率是生物技术领域中的一个巨大的挑战。除了分子聚集外,在折叠过程中所形成的二硫键错配分子是导致低复性率的另一个主要原因。氧化重折叠机制的阐明为解决此问题提供了有益的启示。如上所述,在折叠的后期,二硫键的形成决定于折叠中间体的构象,类天然、有柔性的结构有利于天然二硫键形成和正确折叠,具有这类结构的分子为有效的折叠中间体,最终都能转变为天然产物;而无效折叠中间体往往具有稳定的结构,使巯基、二硫键内埋妨碍二硫键重排,并因能垒的障碍不利于进一步折叠。因此,降低无效折叠中间体的稳定性使之转变为有效折叠中间体是提高含二硫键蛋白质复性率的一条基本原则,实验证明,碱性pH、低温、降低蛋白质稳定性的试剂、蛋白质二硫键异构酶、改变蛋白质一级结构是实现这一原则的有效手段。此外,这里还就氧化重折叠的基础和应用研究的前景进行了讨论。     

蛋白质氨基酸网络研究进展

氨基酸网络是运用复杂网络工具对蛋白质结构-功能关系研究的新方法。本文回顾了氨基酸网络中常用网络参量的计算方法,如：度分布,聚集系数,平均最短路径等。结合本研究小组的工作,介绍了常用的网络构建和分析方法,并总结了氨基酸网络在蛋白质折叠以及蛋白质分子对接问题中的应用。最后,分析了氨基酸网络研究目前存在的主要问题,并对未来的工作进行了展望。     

蛋白质氨基酸网络研究进展

氨基酸网络是运用复杂网络工具对蛋白质结构-功能关系研究的新方法。本文回顾了氨基酸网络中常用网络参量的计算方法,如:度分布,聚集系数,平均最短路径等。结合本研究小组的工作,介绍了常用的网络构建和分析方法,并总结了氨基酸网络在蛋白质折叠以及蛋白质分子对接问题中的应用。最后,分析了氨基酸网络研究目前存在的主要问题,并对未来的工作进行了展望。     

从氨基酸序列预测蛋白质折叠速率

蛋白质折叠速率预测是当今生物物理学最具挑战性的课题之一．近年来,许多科研工作者开展了大量的研究工作来探索折叠速率的决定因素,许多参数和方法被相继提出．但氨基酸残基间的相互作用、氨基酸的序列顺序等信息对折叠速率的影响从未被提及．采用伪氨基酸组成的方法提取氨基酸的序列顺序信息,利用蒙特卡洛方法选择最佳特征因子,建立线性回归模型进行折叠速率预测．该方法能在不需要任何(显示)结构信息的情况下,直接从蛋白质的氨基酸序列出发对折叠速率进行预测．在Jackknife交互检验方法的验证下,对含有99个蛋白质的数据集,发现折叠速率的预测值与实验值有很好的相关性,相关系数能达到0.81,预测误差仅为2.54．这一精度明显优于其他基于序列的方法,充分说明蛋白质的序列顺序信息是影响蛋白质折叠速率的重要因素．     

基于去折叠自由能的蛋白质结构域划分方法——适用于连续与不连续结构域

结构域是蛋白质的一个结构层次 ,可以看作是蛋白质结构、折叠、功能、进化和设计的基本单位。大多数的蛋白质都可分为若干个结构域 ,结构域的不同组合使蛋白质具有不同的三级结构并具有不同的功能。蛋白质结构域的划分在理论与应用上都具有重要意义 ,但目前对结构域的划分还没有一个十分理想的方法。作者曾经发展了一种通过计算去折叠自由能划分蛋白质结构域的方法 ,但该方法只适用于连续双结构域的划分。现在 ,作者通过构造氨基酸残基相互作用矩阵 ,并进行对应分析 (correspondenceanalysis) ,然后根据去折叠自由能和一些经验打分函数对蛋白质进行切割和优选 ,发展了可以同时处理连续和不连续结构域的划分方法。该方法与晶体结构作者手工分析相比较 ,二者的结果有 76 %的相似。     

蛋白质折叠速率与其氨基酸序列极性的关系

以大肠杆菌60个蛋白酶以及几种常见病毒（SARS病毒、艾滋病病毒、丙型肝炎病毒及乙型肝炎病毒）各蛋白质序列中的所有α-螺旋和β-折叠片段为研究对象,计算了各片段的折叠速率和平均极性,分别在各物种的α-螺旋和β-折叠两类二级结构片段中分析了二者的相关性。得到结论：不论是大肠杆菌中的蛋白酶还是病毒蛋白,其中的两类氨基酸片段的平均极性与折叠速率都是极显著相关的：对于所有的α片段,二者呈线性正相关,而对于所有的β片段,二者成线性负相关。结果证实了在蛋白质折叠中,氨基酸的极性起着重要的作用。     

Predicting the subcellular localization of human proteins using machine learning and exploratory data analysis

Identifying the subcellular localization of proteins is particularly helpful in the functional annotation of gene products. In this study, we use Machine Learning and Exploratory Data Analysis （EDA） techniques to examine and characterize amino acid sequences of human proteins localized in nine cellular compartments. A dataset of 3,749 protein sequences representing human proteins was extracted from the SWISS-PROT database. Feature vectors were created to capture specific amino acid sequence characteristics. Relative to a Support Vector Machine, a Multi-layer Perceptron, and a Naive Bayes classifier, the C4.5 Decision Tree algorithm was the most consistent performer across all nine compartments in reliably predicting the subcellular localization of proteins based on their amino acid sequences （average Precision=0.88; average Sensitivity=0.86）. Furthermore, EDA graphics characterized essential features of proteins in each compartment. As examples, proteins localized to the plasma membrane had higher proportions of hydrophobic amino acids; cytoplasmic proteins had higher proportions of neutral amino acids; and mitochondrial proteins had higher proportions of neutral amino acids and lower proportions of polar amino acids. These data showed that the C4.5 classifier and EDA tools can be effective for characterizing and predicting the subcellular localization of human proteins based on their amino acid sequences.     

Advances in the molecular biology of plant seed storage proteins

Plant seed storage proteins were among the first proteins to be isolated (20); however, only recently, as a result of using molecular biology techniques, have the amino acid sequences of many of these proteins been determined. With the accumulation of amino acid sequence data for many vicilin-type storage proteins much has been learned concerning the location of conserved amino acid regions and other regions which can tolerate amino acid sequence variation. Combining this knowledge with recent advances in plant gene transfer technologies will allow molecular biologists to correct (by using amino acid replacement mutations) the sulfur amino acid deficiency inherent to bean seed storage proteins. The development of more nutritious soybean and common bean seeds will be of benefit to programs involving human and animal nutrition.     

Distribution of amino acid residues in the primary protein structure

The amino acid composition and sequence in primary structure of 180 proteins have been studied. It is shown that the distribution of amino acid residues is near to a random one, i.e. it is determined by the amino acid composition. The ratio between statistical and unique character of protein primary structures has been discussed. The amino acid sequence is suggested to be unique in fibrous proteins. In contrast the amino acid sequence in globular proteins is a statistical one. The statistical character of amino acids distribution in globular proteins explains the possibility of sensible text generation under the frame shift mutations, deletions and insertions.     

Comparative characterization of random‐sequence proteins consisting of 5, 12, and 20 kinds of amino acids

Screening of functional proteins from a random‐sequence library has been used to evolve novel proteins in the field of evolutionary protein engineering. However, random‐sequence proteins consisting of the 20 natural amino acids tend to aggregate, and the occurrence rate of functional proteins in a random‐sequence library is low. From the viewpoint of the origin of life, it has been proposed that primordial proteins consisted of a limited set of amino acids that could have been abundantly formed early during chemical evolution. We have previously found that members of a random‐sequence protein library constructed with five primitive amino acids show high solubility (Doi et al., Protein Eng Des Sel 2005;18:279–284). Although such a library is expected to be appropriate for finding functional proteins, the functionality may be limited, because they have no positively charged amino acid. Here, we constructed three libraries of 120‐amino acid, random‐sequence proteins using alphabets of 5, 12, and 20 amino acids by preselection using mRNA display (to eliminate sequences containing stop codons and frameshifts) and characterized and compared the structural properties of random‐sequence proteins arbitrarily chosen from these libraries. We found that random‐sequence proteins constructed with the 12‐member alphabet (including five primitive amino acids and positively charged amino acids) have higher solubility than those constructed with the 20‐member alphabet, though other biophysical properties are very similar in the two libraries. Thus, a library of moderate complexity constructed from 12 amino acids may be a more appropriate resource for functional screening than one constructed from 20 amino acids.     

Protein surface amino acid compositions distinctively differ between thermophilic and mesophilic bacteria

One of the well-known observations of proteins from thermophilic bacteria is the bias of the amino acid composition in which charged residues are present in large numbers, and polar residues are scarce. On the other hand, it has been reported that the molecular surfaces of proteins are adapted to their subcellular locations, in terms of the amino acid composition. Thus, it would be reasonable to expect that the differences in the amino acid compositions between proteins of thermophilic and mesophilic bacteria would be much greater on the protein surface than in the interior. We performed systematic comparisons between proteins from thermophilic bacteria and mesophilic bacteria, in terms of the amino acid composition of the protein surface and the interior, as well as the entire amino acid chains, by using sequence information from the genome projects. The biased amino acid composition of thermophilic proteins was confirmed, and the differences from those of mesophilic proteins were most obvious in the compositions of the protein surface. In contrast to the surface composition, the interior composition was not distinctive between the thermophilic and mesophilic proteins. The frequency of the amino acid pairs that are closely located in the space was also analyzed to show the same trend of the single amino acid compositions. Interestingly, extracellular proteins from mesophilic bacteria showed an inverse trend against thermophilic proteins (i.e. a reduced number of charged residues and rich in polar residues). Nuclear proteins from eukaryotes, which are known to be abundant in positive charges, showed different compositions as a whole from the thermophiles. These results suggest that the bias of the amino acid composition of thermophilic proteins is due to the residues on the protein surfaces, which may be constrained by the extreme environment.     

The N-terminal sequence of three coat proteins of foot-and-mouth disease virus.

The N-terminal section of the amino acids sequences of three coat proteins of foot-and-mouth disease virus were determined and compared with the first ten amino acids of the corresponding Mengo virus proteins. In the proteins of the two viruses beginning with aspartic acid, five of ten amino acids are in identical positions.     

The mitochondrial pool of free amino acids reflects the composition of mitochondrial DNA-encoded proteins: indication of a post- translational quality control for protein synthesis

Mitochondria can synthesize a limited number of proteins encoded by mtDNA (mitochondrial DNA) by using their own biosynthetic machinery, whereas most of the proteins in mitochondria are imported from the cytosol. It could be hypothesized that the mitochondrial pool of amino acids follows the frequency of amino acids in mtDNA-encoded proteins or, alternatively, that the profile is the result of the participation of amino acids in pathways other than protein synthesis (e.g. haem biosynthesis and aminotransferase reactions). These hypotheses were tested by evaluating the pool of free amino acids and derivatives in highly-coupled purified liver mitochondria obtained from rats fed on a nutritionally adequate diet for growth. Our results indicated that the pool mainly reflects the amino acid composition of mtDNA-encoded proteins, suggesting that there is a post-translational control of protein synthesis. This conclusion was supported by the following findings: (i) correlation between the concentration of free amino acids in the matrix and the frequency of abundance of amino acids in mtDNA-encoded proteins; (ii) the similar ratios of essential-to-non-essential amino acids in mtDNA-encoded proteins and the mitochondrial pool of amino acids; and (iii), lack of a correlation between codon usage or tRNA levels and amino-acid concentrations. Quantitative information on the mammalian mitochondrial content of amino acids, such as that presented in the present study, along with functional studies, will help us to better understand the pathogenesis of mitochondrial diseases or the biochemical implications in mitochondrial metabolism.     

Misincorporation of amino acid analogues into proteins by biosynthesis

Despite astounding diversity in their structure and function, proteins are constructed from 22 protein or ‘canonical’ amino acids. Hundreds of amino acid analogues exist; many occur naturally in plants, some are synthetically produced or can be produced in vivo by oxidation of amino acid side-chains. Certain structural analogues of the protein amino acids can escape detection by the cellular machinery for protein synthesis and become misincorporated into the growing polypeptide chain of proteins to generate non-native proteins. In this review we seek to provide a comprehensive overview of the current knowledge on the biosynthetic incorporation of amino acid analogues into proteins by mammalian cells. We highlight factors influencing their incorporation and how the non-native proteins generated can alter cell function. We examine the ability of amino acid analogues, representing those commonly found in damaged proteins in pathological tissues, to be misincorporated into proteins by cells in vitro, providing us with a useful tool in the laboratory to generate modified proteins representing those present in a wide-range of pathologies. We also discuss the evidence for amino acid analogue incorporation in vivo and its association with autoimmune symptoms. We confine the review to studies in which the synthetic machinery of cell has not been modified to accept non-protein amino acids.     

Using Genome-Wide Protein Sequence Data to Predict Amino Acid Conservation

For most proteins, multiple sequence alignments are a viable method to identify functionally and structurally important amino acids, but for most organisms, there is a subset of proteins that are unique or found in a few closely related organisms. For these proteins, it is not possible to produce sequence alignments that are useful in identifying functionally or structurally important amino acids. We have investigated the relationship between amino acid conservation and five factors (the amino acid’s identity, N-terminal neighbor, C-terminal neighbor, the local hydropathy of surrounding amino acids, and the local expected net charge of the surrounding amino acids based on the primary sequence) in Escherichia coli proteins. For four of the factors examined (all but the amino acid’s identity), there is a significant relationship with conservation for some of the standard 20 amino acids. Using the combination of all five factors, we show that it is possible to calculate a score based on the primary sequences of a subset of E. coli proteins that has statistically significant predictive value with respect to predicting conserved amino acids in other E. coli proteins and Saccharomyces cerevisiae proteins. As these five variables show significant relationships with conservation, we have termed them conservation factors. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.