k子串离散源结合加权KNN算法预测膜蛋白类型

膜蛋白是生物膜功能的主要体现者,是细胞执行各种功能的物质基础,在细胞中发挥着至关重要的作用.分类预测未知类型的膜蛋白对于生物学相关研究具有指导性意义,是膜蛋白结构与功能研究领域的一项重要基础性工作.针对膜蛋白分类预测问题,利用k子串离散源的方法对膜蛋白序列进行特征提取,并融合最小离散增量方法和加权K近邻算法构建一种新型的膜蛋白分类预测模型,在自检验、Jackknife检验和独立测试集检验三种典型的检验方式下,预测准确率分别为99.95%、86.16%和98.36%.实验结果表明,k子串离散源方法能够有效提取膜蛋白序列的特征信息,与现有方法相比,该分类模型具有较高的分类预测成功率.     

随机森林方法预测膜蛋白类型

膜蛋白的类型与其功能是密切相关的,因此膜蛋白类型的预测是研究其功能的重要手段,从蛋白质的氨基酸序列出发对膜蛋白的类型进行预测有重要意义。文章基于蛋白质的氨基酸序列,将组合离散增量和伪氨基酸组分信息共同作为预测参数,采用随机森林分类器,对8类膜蛋白进行了预测。在Jackknife检验下的预测精度为86.3%,独立检验的预测精度为93.8%,取得了好于前人的预测结果。     

分枝杆菌膜蛋白相关抗结核药物靶标的研究进展

结核病是由结核分枝杆菌引起的慢性传染病。当前结核病耐药等问题愈加严重,基于新靶点的抗结核新药研发也变得尤为重要。分枝杆菌膜蛋白是镶嵌于细胞膜磷脂双层或与脂双层结合的一类蛋白,参与细胞结构合成、物质跨膜转运、催化等重要的生物学功能,并在宿主感染中参与免疫识别、免疫逃逸、毒力因子释放等致病机制。另一方面,膜蛋白具有特定的拓扑结构和细胞定位,药物靶标可及性强,因此膜蛋白是抗结核药物作用的理想靶标。本文就分枝杆菌膜蛋白在细胞壁合成、物质跨膜转运、细菌休眠、细菌与宿主互作及分泌系统相关研究进展进行综述,旨在为抗结核药物研发提供新思路。     

结核分枝杆菌膜蛋白的异源表达与纯化研究进展

膜蛋白是一类与生物膜相互作用、具有重要功能和独特结构的蛋白质。异源表达纯化一直是了解膜蛋白结构和功能的重要瓶颈。结核分枝杆菌作为典型的胞内致病菌,其膜蛋白的研究具有很好的代表性以及重要意义。目前用于表达膜蛋白的有大肠杆菌、酵母、哺乳动物细胞等表达系统,但结核菌膜蛋白的表达宿主还往往局限于大肠杆菌。异源表达需要综合考虑蛋白的来源、疏水性、跨膜区等特性。低温、加入共表达因子以及改变培养条件有助于结核菌膜蛋白的可溶性表达。另外,包涵体复性也是获得结核菌目的膜蛋白的重要途径。随着新的表达系统,新的促可溶表达策略,新的包涵体复性手段,新的纯化方法的应用,将有更多的膜蛋白异源表达纯化成功,为蛋白质功能研究奠定基础。     

基于压缩氨基酸和支持向量机进行膜蛋白类型识别

膜蛋白是一类结构独特的蛋白质,是细胞执行各种功能的物质基础。根据其在细胞膜上的不同存在方式,主要分为六种类型。本文利用压缩的氨基酸对原始膜蛋白序列进行信息压缩,再对压缩序列进行氨基酸组成和顺序特征的提取,最后采用支持向量机构建分类模型。通过五叠交叉验证的结果表明,该方法对于六种膜蛋白的分类预测,准确度最高可达98％以上,平均预测准确度在85％以上,可有效实现膜蛋白六种类型的划分,为进一步分析膜蛋白的结构和功能奠定基础。     

植物跨膜蛋白研究进展

跨膜蛋白是一类结构独特,在植物细胞中广泛存在,并发挥重要生理功能的蛋白质。综述了植物跨膜蛋白的理化性质、蛋白质结构预测的方法,以及其生理功能的研究进展。随着对植物跨膜蛋白的深入研究,将有助于揭示跨膜蛋白对植物生长发育调控的重要分子机制。     

日本国立传染病研究所有关结核病的新资料

<正>科学家发现了结核分枝杆菌主要膜蛋白Ⅱ的免疫刺激活性。以前观察到麻风分枝杆菌(MMP-ML)的主要膜蛋白Ⅱ和它与牛型分枝杆菌BCG热休克蛋白70(HSP70)的融合物(Fusion-ML)都有免疫原性,能分泌这些蛋白的重组BCG都能有效地抑制麻风分     

基于光激活定位显微镜的膜蛋白鉴定技术

病原菌膜蛋白的原位标记和定位追踪是一项非常繁琐的工作。为了建立一种可以用于快速鉴定膜蛋白、且分辨率达到纳米级别的膜蛋白荧光定位技术,将结核分枝杆菌外膜蛋白OmpA与具有光敏活性的蛋白mEos2m在无致病性的耻垢分枝杆菌中进行融合表达。重组菌固定在载玻片上后,利用405 nm激光激活mEos2m。利用普通荧光体视显微镜、正置荧光显微镜和超分辨率光激活定位显微镜观察OmpA-mEos2m,分析融合蛋白在细菌内的分布情况,并捕获光激活蛋白在细胞膜上释放的光子信号。通过超分辨率光激活定位显微镜,发现OmpA-mEos2m融合蛋白在细胞膜上呈"带"状环绕分布,这是观察到膜蛋白在细胞膜上定位的最直接证据。mEos2m与OmpA融合表达后,并不改变OmpA的膜蛋白属性和定位特征。因此可以将mEos2m用于其他非多聚体膜蛋白的融合和定位研究。可以应用非致病性的耻垢分枝杆菌作为模型,采用高分辨率活菌成像技术,研究致病性的结核分枝杆菌蛋白结构、定位和功能。这是目前为止国内采用光激活定位显微成像技术研究膜蛋白的首次报道。     

一个识别蛋白质折叠模式的SVM分类器

蛋白质折叠模式识别是一种分析蛋白质结构的重要方法。以序列相似性较低的蛋白质为训练集,提取蛋白质序列信息频数及疏水性等信息作为折叠类型特征,从SCOP数据库中已分类蛋白质构建1 393种折叠模式的数据集,采用SVM预测蛋白质1 393种折叠模式。封闭测试准确率达99.612 2%,基于SCOP的开放测试准确率达79.632 9%。基于另一个权威测试集的开放测试折叠准确率达64.705 9%,SCOP类准确率达76.470 6%,可以有效地对蛋白质折叠模式进行预测,从而为蛋白质从头预测提供参考。     

结核分枝杆菌生物被膜基质及潜在的药物靶点和治疗策略

持留性是结核分枝杆菌产生耐药和复发的重要原因之一.分枝杆菌的持留性与生物被膜的形成密切相关,对生物被膜的研究将有助于新型抗结核药物的开发.细胞外多糖、蛋白、DNA和脂质是结核分枝杆菌生物被膜细胞外基质的重要组成成分.本文阐述了结核分枝杆菌生物被膜基质的组成成分及基于这些成分潜在的药物靶点和治疗策略,希望为结核分枝杆菌生物被膜基质的生物学功能的研究带来新的思考.     

NMR structures of polytopic integral membrane proteins

Membrane proteins represent up to 30% of the proteins in all organisms, they are involved in many biological processes and are the molecular targets for around 50% of validated drugs. Despite this, membrane proteins represent less than 1% of all high-resolution protein structures due to various challenges associated with applying the main biophysical techniques used for protein structure determination. Recent years have seen an explosion in the number of high-resolution structures of membrane proteins determined by NMR spectroscopy, especially for those with multiple transmembrane-spanning segments. This is a review of the structures of polytopic integral membrane proteins determined by NMR spectroscopy up to the end of the year 2010, which includes both β-barrel and α-helical proteins from a number of different organisms and with a range in types of function. It also considers the challenges associated with performing structural studies by NMR spectroscopy on membrane proteins and how some of these have been overcome, along with its exciting potential for contributing new knowledge about the molecular mechanisms of membrane proteins, their roles in human disease, and for assisting drug design.     

NMR structures of polytopic integral membrane proteins

Abstract

Membrane proteins represent up to 30% of the proteins in all organisms, they are involved in many biological processes and are the molecular targets for around 50% of validated drugs. Despite this, membrane proteins represent less than 1% of all high-resolution protein structures due to various challenges associated with applying the main biophysical techniques used for protein structure determination. Recent years have seen an explosion in the number of high-resolution structures of membrane proteins determined by NMR spectroscopy, especially for those with multiple transmembrane-spanning segments. This is a review of the structures of polytopic integral membrane proteins determined by NMR spectroscopy up to the end of the year 2010, which includes both β-barrel and α-helical proteins from a number of different organisms and with a range in types of function. It also considers the challenges associated with performing structural studies by NMR spectroscopy on membrane proteins and how some of these have been overcome, along with its exciting potential for contributing new knowledge about the molecular mechanisms of membrane proteins, their roles in human disease, and for assisting drug design.     

Quantitative analysis of surface plasma membrane proteins of primary and metastatic melanoma cells

Plasma membrane proteins play critical roles in cell-to-cell recognition, signal transduction and material transport. Because of their accessibility, membrane proteins constitute the major targets for protein-based drugs. Here, we described an approach, which included stable isotope labeling by amino acids in cell culture (SILAC), cell surface biotinylation, affinity peptide purification and LC-MS/MS for the identification and quantification of cell surface membrane proteins. We applied the strategy for the quantitative analysis of membrane proteins expressed by a pair of human melanoma cell lines, WM-115 and WM-266-4, which were derived initially from the primary and metastatic tumor sites of the same individual. We were able to identify more than 100 membrane and membrane-associated proteins from these two cell lines, including cell surface histones. We further confirmed the surface localization of histone H2B and three other proteins by immunocytochemical analysis with confocal microscopy. The contamination from cytoplasmic and other nonmembrane-related sources is greatly reduced by using cell surface biotinylation and affinity purification of biotinylated peptides. We also quantified the relative expression of 62 identified proteins in the two types of melanoma cells. The application to quantitative analysis of membrane proteins of primary and metastatic melanoma cells revealed great potential of the method in the comprehensive identification of tumor progression markers as well as in the discovery of new protein-based therapeutic targets.     

Amino acid composition analysis of secondary transport proteins from Escherichia coli with relation to functional classification,ligand specificity and structure

We have performed an amino acid composition (AAC) analysis of the complete sequences for 235 secondary transport proteins from Escherichia coli, which have functions in the uptake and export of organic and inorganic metabolites, efflux of drugs and in controlling membrane potential. This revealed the trends in content for specific amino acid types and for combinations of amino acids with similar physicochemical properties. In certain proteins or groups of proteins, the so-called spikes of high content for a specific amino acid type or combination of amino acids were identified and confirmed statistically, which in some cases could be directly related to function and ligand specificity. This was prevalent in proteins with a function of multidrug or metal ion efflux. Any tool that can help in identifying bacterial multidrug efflux proteins is important for a better understanding of this mechanism of antibiotic resistance. Phylogenetic analysis based on sequence alignments and comparison of sequences at the N- and C-terminal ends confirmed transporter Family classification. Locations of specific amino acid types in some of the proteins that have crystal structures (EmrE, LacY, AcrB) were also considered to help link amino acid content with protein function. Though there are limitations, this work has demonstrated that a basic analysis of AAC is a useful tool to use in combination with other computational and experimental methods for classifying and investigating function and ligand specificity in a large group of transport or other membrane proteins, including those that are molecular targets for development of new drugs.     

A family of extracytoplasmic proteins that allow transport of large molecules across the outer membranes of gram-negative bacteria.

Seventeen fully sequenced and two partially sequenced extracytoplasmic proteins of purple, gram-negative bacteria constitute a homologous family termed the putative membrane fusion protein (MFP) family. Each such protein apparently functions in conjunction with a cytoplasmic membrane transporter of the ATP-binding cassette family, major facilitator superfamily, or heavy metal resistance/nodulation/cell division family to facilitate transport of proteins, peptides, drugs, or carbohydrates across the two membranes of the gram-negative bacterial cell envelope. Evidence suggests that at least some of these transport systems also function in conjunction with a distinct outer membrane protein. We report here that the phylogenies of these proteins correlate with the types of transport systems with which they function as well as with the natures of the substrates transported. Characterization of the MFPs with respect to secondary structure, average hydropathy, and average similarity provides circumstantial evidence as to how they may allow localized fusion of the two gram-negative bacterial cell membranes. The membrane fusion protein of simian virus 5 is shown to exhibit significant sequence similarity to representative bacterial MFPs.     

A Multi-label Classifier for Prediction Membrane Protein Functional Types in Animal

Membrane protein is an important composition of cell membrane. Given a membrane protein sequence, how can we identify its type(s) is very important because the type keeps a close correlation with its functions. According to previous studies, membrane protein can be divided into the following eight types: single-pass type I, single-pass type II, single-pass type III, single-pass type IV, multipass, lipid-anchor, GPI-anchor, peripheral membrane protein. With the avalanche of newly found protein sequences in the post-genomic age, it is urgent to develop an automatic and effective computational method to rapid and reliable prediction of the types of membrane proteins. At present, most of the existing methods were based on the assumption that one membrane protein only belongs to one type. Actually, a membrane protein may simultaneously exist at two or more different functional types. In this study, a new method by hybridizing the pseudo amino acid composition with multi-label algorithm called LIFT (multi-label learning with label-specific features) was proposed to predict the functional types both singleplex and multiplex animal membrane proteins. Experimental result on a stringent benchmark dataset of membrane proteins by jackknife test show that the absolute-true obtained was 0.6342, indicating that our approach is quite promising. It may become a useful high-through tool, or at least play a complementary role to the existing predictors in identifying functional types of membrane proteins.     

Identifying the membrane proteome of HIV-1 latently infected cells

Profiling integral plasma membrane proteins is of particular importance for the identification of new biomarkers for diagnosis and for drug development. We report in this study the identification of surface markers by performing comparative proteomics of established human immunodeficiency virus-1 (HIV-1) latent cell models and parental cell lines. To this end we isolated integral membrane proteins using a biotin-directed affinity purification method. Isolated proteins were separated by two-dimensional gel electrophoresis and identified by matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) after in gel digestion. Seventeen different proteins were found to vary on the surface of T-cells due to HIV-1 infection. Of these proteins, 47% were integral membrane proteins, and 18% were membrane-associated. Through the use of complementary techniques such as Western blotting and fluorescent staining, we confirmed the differential expression of some of the proteins identified by MALDI-TOF including Bruton's tyrosine kinase and X-linked inhibitor of apoptosis. Finally, using phosphatidylinositol 3-kinase inhibitors and flavopiridol to inhibit Bruton's tyrosine kinase localization at the membrane and X-linked inhibitor of apoptosis protein expression, respectively, we showed that HIV-1 latently infected cells are more sensitive to these drugs than uninfected cells. This suggests that HIV-1 latently infected cells may be targeted with drugs that alter several pathways that are essential for the establishment and maintenance of latency.     

Using auto covariance method for functional discrimination of membrane proteins based on evolution information

Membrane transporters are critical in living cells. Therefore, the discrimination of the types of membrane proteins based on their functions is of great importance both for helping genome annotation and providing a supplementary role to experimental researchers to gain insight into membrane proteins’ function. There are a lot of computational methods to facilitate the identification of the functional types of membrane proteins. However, in these methods, the local sequence environment was not integrated into the constructed model. In this study, we described a new strategy to predict the functional types of membrane proteins using a model based on auto covariance and position-specific scoring matrix. The novelty of the presented approach is considering the distribution of different positions of functional conservation sites in protein sequences. Thereby, this model adequately takes into account the long-range correlation between such sites during sequential evolution. Fivefold cross-validation test shows that this method greatly improves the prediction accuracy and achieves an acceptable prediction accuracy of 87.51%. The result indicates that the current approach might be an effective tool for predicting the functional types of membrane proteins only using the primary sequences. The code and dataset used in this article are freely available at .     

A Multilabel Model Based on Chou’s Pseudo–Amino Acid Composition for Identifying Membrane Proteins with Both Single and Multiple Functional Types

Predicting membrane protein type is a meaningful task because this kind of information is very useful to explain the function of membrane proteins. Due to the explosion of new protein sequences discovered, it is highly desired to develop efficient computation tools for quickly and accurately predicting the membrane type for a given protein sequence. Even though several membrane predictors have been developed, they can only deal with the membrane proteins which belong to the single membrane type. The fact is that there are membrane proteins belonging to two or more than two types. To solve this problem, a system for predicting membrane protein sequences with single or multiple types is proposed. Pseudo–amino acid composition, which has proven to be a very efficient tool in representing protein sequences, and a multilabel KNN algorithm are used to compose this prediction engine. The results of this initial study are encouraging.