颗粒裂解肽G13结构域在大肠杆菌中的高效融合表达

为高效表达颗粒裂解肽G13结构域并避免G13对宿主菌的毒性, 将人工合成的编码G13的基因片段, PCR扩增后克隆于原核表达载体pThioHisA中, 构建了重组表达载体pThioHisA-G13, 将其转化于大肠杆菌BL21(DE3)中, 经IPTG诱导表达融合蛋白Trx-G13, 表达产物以包涵体的形式存在, 其表达量约占细菌总蛋白的58%。包涵体蛋白经 8 mol/L尿素溶解后, 再经CNBr切割, 阳离子交换层析, 得到纯化的重组G13结构域。琼脂糖扩散法检测表明重组G13结构域多肽具有抗菌活性。     

人颗粒裂解肽片段在大肠杆菌中的表达

目的：建立颗粒裂解肽（NKG5）的原核表达载体系统,并在大肠杆菌中获得表达。方法：采用寡核苷酸合成、PCR扩增得到NKG5编码序列,克隆到pGEM-T载体上,经测序正确后,再切下编码序列连接到重组表达载体pGEx-4T-1中,转化大肠杆菌BL21,用IPTG诱导重组工程菌表达,采用谷胱甘肽偶联的Sepharose 4B纯化重组蛋白。结果：重组菌株可以表达GST-NKG5融合蛋白,用免疫印迹反应鉴定纯化的融合蛋白,在相对分子质量34000处有一条带。结论：获得了在大肠杆菌中低表达的颗粒裂解肽融合蛋白,为后续研究奠定了基础。     

蛋白质PX结构域的结构和功能

本文重点介绍了近年不断发现的许多蛋白质结构中含有一个特异的结构域（hox homolog)－PX结构域。蛋白质通过PX结构域与膜肌醇磷脂结合靶蛋白质结合到细胞膜上,然后发挥蛋白质的各自功能。现已鉴定含PX结构域的蛋白质约有100多种,这些蛋白质参与蛋白质转运和信号转导。     

蛋白质结构与功能中的结构域

结构域是蛋白质亚基结构中的紧密球状区域.结构域作为蛋白质结构中介于二级与三级结构之间的又一结构层次,在蛋白质中起着独立的结构单位、功能单位与折叠单位的作用.在复杂蛋白质中,结构域具有结构与功能组件与遗传单位的作用.结构域层次的研究将会促进蛋白质结构与功能关系、蛋白质折叠机制以及蛋白质设计的研究.     

人类蛋白质结构互作网络——结构域对网络拓扑与蛋白质功能的影响

高通量的蛋白质互作数据与结构域互作数据的出现,使得在蛋白质组学领域内研究人类蛋白质结构互作网络,进一步揭示蛋白质结构与功能间的潜在关系成为可能.蛋白质上广泛分布的结构域被认为是蛋白质结构、功能以及进化的基本功能单元.然而,结合蛋白质的结构信息(例如蛋白质结构域数目、长度和覆盖率等)来研究这些表象后的内部机制仍然面临着挑战.将蛋白质分为单结构域蛋白质与多结构域蛋白质,并进一步结合蛋白质互作信息与结构域互作信息构建了人类蛋白质结构互作网络;通过与人类蛋白质互作网络进行比较,研究了人类蛋白质结构互作网络的特殊结构特征;对于单结构域蛋白质与多结构域蛋白质,分别进行了功能富集分析、功能离散度分析以及功能一致性分析等.结果发现,将结构域互作信息综合考虑进来后,人类蛋白质结构互作网络可以提供更多的单纯的蛋白质互作网络无法提供的细节信息,揭示蛋白质互作网络的复杂性.     

TAT蛋白质转导结构域与SV40启动子特异的三锌指结构融合蛋白的表达与纯化

利用蛋白质转导结构域(PTDs)可以将与之融合表达的蛋白质直接送入细胞中。将通过筛选噬菌体展示锌指库得到的特异作用于SV40启动子上9bp序列的三锌指结构的序列插入含有TAT蛋白的蛋白质转导结构域的表达载体pET—TAT-NLS中,构建融合蛋白的表达载体pET-TAT-NLS—clone3。融合蛋白在E．coli BL21(DE3)中得到了可溶性表达,含量约占总蛋白的18％;并通过镍亲和凝胶层析柱得到了较好的纯化融合蛋白。     

人源CBX7功能结构域的重组表达与纯化

CBX7(chromobox 7)在细胞寿命延长和癌症发生中起着重要的调控作用。然而,获取足量的全长CBX7蛋白并用于结构研究极为艰难。实验阐述了CBX7功能结构域CBX7(aa 145～227)重组表达载体构建的详细过程。同时,通过Ni-NTA亲和层析对融合目的蛋白进行了纯化,并利用SDS-PAGE及Western-blot进行了鉴定分析。纯化后的融合蛋白样品通过离子交换和分子筛层析进一步分离剩余杂质。本实验得到的高浓度CBX7蛋白可用于结晶,为后续CBX7的结构和功能研究奠定了基础。     

人源Fank1蛋白质FN3结构域多肽的原核表达，纯化及晶体筛选

目的纯化人源Fank1（fibronectin type Ⅲ and ankyrin repeat domain1）蛋白质N端FN3（fibronectin typeⅢ,Ⅲ型纤黏连蛋白）结构域蛋白,用于晶体生长的三维结构分析。方法将FN3结构域基因片段克隆至原核表达载体pGEX-6P-1中,将菌落PCR和测序鉴定正确的重组质粒转化E.coli BL21（DE3）后获得表达菌株。该菌株经IPTG诱导高效表达出带有GST标签的可溶性的融合蛋白,经过Glutathione Sepha-rose^TM 4B亲和层析、Hiload16／60 superdex200分子筛层析纯化后,蛋白纯度达到95％以上。结果纯化蛋白采用悬滴气相扩散法得到棒状晶体。结论成功制备了高纯度FN3蛋白,获得FN3蛋白质晶体,为进一步的三维结构解析及Fank1功能研究奠定了基础。     

APP17肽对β—淀粉样肽及有关蛋白质表达的影响

本研究选用人类野生型SY5Y及SY5YA4CT基因转染细胞,应用免疫沉淀Western Blot等分析方法研究APP17肽对β-淀粉样肽及有关蛋白质如IDE,NT－3,NF表达的影响,探讨其影响神经元存活和退变的可能机理,结果发现,APP17肽能抑制转染细胞Aβ胞外分泌,并能促进野生型SY5Y细胞中IDE的表达,同时对内源性NT－3和NF的表达也有促进作用,提示：APP17肽抑制Aβ分泌和促进内源性神经营养因子的表达可能是其支持神经元存活,改善神经退变的机理之一。     

重组蛋白G Fc结合区单结构域的纯化及理化性质

蛋白 G 是存在于链球菌 C 群和 G 群胞膜上的一种分子量为65kD 的膜蛋白,完整的蛋白 G 分子主要由四部分组成,其中第三部分能与许多动物的 IgG Fc段特异结合。近年来,蛋白 G 的应用研究已展示出广阔前景,它一方面可与多种标记物(如酶、放射性同位素、胶体金等)连接,用于免疫分析;另一方面,可用作纯化单克隆抗体及多克隆抗体的亲和配基。但是有关蛋白 G 的空间结构及其与 IgG Fc 的结合机制     

链球菌蛋白G的构建、重组表达及鉴定

化学合成链球茵蛋白G的C3D基因片段,通过分子生物学的方法对蛋白G（proteinG）的C3片段进行PCR扩增,拼接形成含有两个和三个重复C3片段的重组链球茵蛋白G,C3片段间以链接区D连接,即形成C3DC3和C3DC3DC3的形式,进而克隆到质粒pET21中,在大肠杆菌BL21（DE3）中表达。重组表达的蛋白经过DEAE—Sepharose和IgG—Sepharose纯化,得到纯化的重组蛋白。采用非竞争性酶免疫法对重组蛋白与不同来源IgG的结合常数进行测定,实验结果显示两种重组链球茵蛋白G均可有效地与小鼠、兔及山羊等多种不同来源抗体特异性结合。这些实验结果为下一步研究奠定了基础。     

大肠杆菌发酵生产重组人颗粒溶素

目的:在FUS-50L生物反应器中利用补料分批培养技术培养表达含重组质粒pET28a( )-GNLY的大肠杆菌BL21(DE3)pLysS株,生产重组颗粒溶素(GNLY)。方法:选取含pET28a( )-GNLY的BL21(DE3)pLysS菌株单个克隆分级培养,将制备的二级种子液接种于发酵罐中。在发酵过程中,控制溶氧为30%～50%,温度为37℃;在基础培养基内生长4h后,补加以甘油为碳源的补料,继续生长到11h;加入葡萄糖至终浓度为1%,30℃诱导表达6h;收集菌体,纯化制备目的蛋白。利用Western印迹检测重组蛋白的抗原性,用CFU方法检测其生物学活性。结果:发酵液中最终菌体密度达80g/L;纯化所得重组蛋白约占菌体总蛋白的5%,含量为60mg/L;经鉴定所获重组颗粒溶素有较好的免疫学活性和生物学活性。结论:用含重组质粒pET28a( )-GNLY的大肠杆菌BL21(DE3)pLysS表达系统,可得到具有生物活性的重组颗粒溶素,为大批量生产提供了条件。     

13C and 15N chemical shift assignments and secondary structure of the B3 immunoglobulin-binding domain of streptococcal protein G by magic-angle spinning solid-state NMR spectroscopy

Complete ¹³C and ¹⁵N assignments of the B3 IgG-binding domain of protein G (GB3) in the microcrystalline solid phase, obtained using 2D and 3D MAS NMR, are presented. The chemical shifts are used to predict the protein backbone conformation and compared with solution-state shifts. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Delineation of modular proteins: domain boundary prediction from sequence information

The delineation of domain boundaries of a given sequence in the absence of known 3D structures or detectable sequence homology to known domains benefits many areas in protein science, such as protein engineering, protein 3D structure determination and protein structure prediction. With the exponential growth of newly determined sequences, our ability to predict domain boundaries rapidly and accurately from sequence information alone is both essential and critical from the viewpoint of gene function annotation. Anyone attempting to predict domain boundaries for a single protein sequence is invariably confronted with a plethora of databases that contain boundary information available from the internet and a variety of methods for domain boundary prediction. How are these derived and how well do they work? What definition of 'domain' do they use? We will first clarify the different definitions of protein domains, and then describe the available public databases with domain boundary information. Finally, we will review existing domain boundary prediction methods and discuss their strengths and weaknesses.     

A machine learning based method for the prediction of G protein-coupled receptor-binding PDZ domain proteins

G protein-coupled receptors (GPCRs) are part of multi-protein networks called ‘receptosomes’. These GPCR interacting proteins (GIPs) in the receptosomes control the targeting, trafficking and signaling of GPCRs. PDZ domain proteins constitute the largest protein family among the GIPs, and the predominant function of the PDZ domain proteins is to assemble signaling pathway components into close proximity by recognition of the last four C-terminal amino acids of GPCRs. We present here a machine learning based approach for the identification of GPCR-binding PDZ domain proteins. In order to characterize the network of interactions between amino acid residues that contribute to the stability of the PDZ domain-ligand complex and to encode the complex into a feature vector, amino acid contact matrices and physicochemical distance matrix were constructed and adopted. This novel machine learning based method displayed high performance for the identification of PDZ domain-ligand interactions and allowed the identification of novel GPCR-PDZ domain protein interactions.     

Tertiary structure prediction of the KIX domain of CBP using Monte Carlo simulations driven by restraints derived from multiple sequence alignments

Using a recently developed protein folding algorithm, a prediction of the tertiary structure of the KIX domain of the CREB binding protein is described. The method incorporates predicted secondary and tertiary restraints derived from multiple sequence alignments in a reduced protein model whose conformational space is explored by Monte Carlo dynamics. Secondary structure restraints are provided by the PHD secondary structure prediction algorithm that was modified for the presence of predicted U-turns, i.e., regions where the chain reverses global direction. Tertiary restraints are obtained via a two-step process: First, seed side-chain contacts are identified from a correlated mutation analysis, and then, a threading-based algorithm expands the number of these seed contacts. Blind predictions indicate that the KIX domain is a putative three-helix bundle, although the chirality of the bundle could not be uniquely determined. The expected root-mean-square deviation for the correct chirality of the KIX domain is between 5.0 and 6.2 Å. This is to be compared with the estimate of 12.9 Å that would be expected by a random prediction, using the model of F. Cohen and M. Sternberg (J. Mol. Biol. 138:321–333, 1980). Proteins 30:287–294, 1998. © 1998 Wiley-Liss, Inc.     

Coordinate expression of the alpha and beta subunits of heterotrimeric G proteins involves regulation of protein degradation in CHO cells

Individual cell types express a characteristic balance between heterotrimeric G protein alpha and betagamma subunits, but little is known about the regulatory mechanism. We systemically examined the regulatory mechanism in CHO cells. We found that expression of Galphas, Galphai2, and Galphaq proteins increased in direct proportion to the increase of Gbeta1gamma2 overexpressed transiently. Expression of Gbeta protein also increased following overexpression of Galphas, Galphai2, and Galphaq. The Gbetagamma overexpression stimulated degradation of Gbeta in contrast to reduction of Galphas degradation. We conclude that coordinate expression of the G protein subunits involves regulation of protein degradation via proteasome in CHO cells.     

蜘蛛丝蛋白的模块结构性能和重组表达

蜘蛛丝是一类天然蛋白质纤维,具有独特的机械性能（高强度、高弹性和高断裂功等）和卓著的生物学特性（生物可降解性和与生物组织的相容性等）,在生物医学、材料、纺织和军事等领域都有着很高的潜在应用价值。综述了不同蜘蛛丝蛋白的模块结构特征及与其功能的关系,扼要介绍了目前利用各种基因工程方法表达重组蜘蛛丝蛋白的研究进展。