蛋白质合成中的核糖核酸蛋白质复合物

细胞中的RNA和RNA结合蛋白质(RNA-binding proteins,RBPs)相互作用形成核糖核酸蛋白质(ribonucleoprotein,RNP)复合物。RNP复合物分布广泛,功能众多。蛋白质生物合成包括转录及其调控、mRNA加工转运、tRNA传递、翻译及其调控等,是核酸编码的遗传信息流向活性蛋白质的过程。多种RNA分子参与这一过程,有的与对应的RNA结合蛋白质形成RNP复合物。RNP复合物的多样性和重要功能在此得到了最好的体现。该文以其中起核心作用的RNA分子为主线,对蛋白质合成中的RNP复合物进行了综述。     

蛋白质复合物结构预测的集成分子对接方法

蛋白质分子间相互作用与识别是当前生命科学研究的热点,分子对接方法是研究这一问题的有效手段．为了推进分子对接方法的发展,欧洲生物信息学中心组织了国际蛋白质复合物结构预测（CAPRI）竞赛．通过参加CAPRI竞赛,逐步摸索出了一套用于蛋白质复合物结构预测的集成蛋白质一蛋白质分子对接方法HoDock,它包括结合位点预测、初始复合物结构采集、精细复合物结构采集、结构成簇和打分排序以及最终复合物结构挑选等主要步骤．本文以最近的CAPRI Target 39为例,具体说明该方法的主要步骤和应用．该方法在CAPRI Target 39竞赛中取得了比较好的结果,预测结构Model 10是所有参赛小组提交的366个结构中仅有的3个正确结构之一,其配体均方根偏差（L_Rmsd）为0．25nm．在对接过程中,首先用理论预测和实验信息相结合的方法来寻找蛋白质结合位点残基,确认CAPRI Target 39A链的A31TRP和A191HIS,B链的B512ARG和B531ARG为可能结合位点残基．同时,用ZDock程序做不依赖结合位点的初步全局刚性对接．然后,根据结合位点信息进行初步局部刚性对接,从全局和局部对接中挑出了11个初始对接复合物结构．进而,用改进的Rosetta Dock程序做精细位置约束对接,并对每组对接中打分排序前200的结构进行成簇聚类．最后,综合分析打分、成簇和结合位点三方面的信息,得到10个蛋白质复合物结构．竞赛结果表明,A191HIS,B512ARG和B531ARG三个结合位点残基预测正确,提交的10个蛋白质复合物结构中有5个复合物受体一配体界面残基预测成功率较高．与其他参赛小组的对接结果比较,表明HoDock方法具有一定优势．这些结果说明我们提出的集成分子对接方法有助于提高蛋白质复合物结构预测的准确率．     

预测蛋白质—蛋白质复合物结构的软对接算法

提出了一种有效的软对接算法 ,用于在已知受体和配体三维结构的条件下预测蛋白质 蛋白质复合物的结构。该算法的分子模型基于Janin提出的简化蛋白质模型 ,并在此基础上有所改进。对蛋白质分子表面的柔性氨基酸残基Arg、Lys、Asp、Glu和Met进行了特殊处理 ,通过软化分子表面的方式考虑了它们的侧链柔性。采用双重过滤技术来排除不合理的对接结构 ,此过滤技术是以复合物界面几何互补性和残基成对偏好性为标准提出的。对所得到的构象进行能量优化 ,之后用打分函数对这些结构进行排序 ,挑选出与复合物天然结构接近的构象。该打分函数包括静电、疏水和范德华相互作用能。用此算法对 2 6个复合物进行了结构预测 ,均找到了近天然结构 ,其中有 2 0个复合物的近天然结构排在了前 10位。改进的分子模型可以在一定程度上描述蛋白质表面残基侧链的柔性 ;双重过滤技术使更多的近天然结构保留下来 ,从而提高了算法成功预测的可能性 ;打分函数可以较合理地评价对接结构。总之 ,此种软对接算法能够对蛋白质分子识别的研究提供有益的帮助。     

RNA和蛋白质的相互作用

RNA与蛋白质的相互作用是许多基本的细胞生理过程得以实现的决定性因素.近年来,随着技术的改进和新方法的建立,RNA和蛋白质的相互作用研究取得了长足进步.目前科研人员已经鉴定了许多RNA上的蛋白质结合位点,也发现了许多蛋白质中的RNA结合结构域,并对它们的结构特征进行了比较详细的研究.这些都为最终探明RNA和蛋白质相互作用的分子机制,从而从本质上认识相关的细胞生理过程打下了坚实的基础.     

RNA—蛋白质相互作用研究的进展

分析原核生物中RNA与蛋白质的相互作用,给了我们很多的信息和启示。到目前为止,大肠杆菌核糖体是研究最多的RNP复合物,而大肠杆菌中的谷氨酰胺基tRNA合成酶和相关的tRNA是目前唯一制成RNA一蛋白质共结晶,并揭示其结构的RNA一蛋白质复合物。最近在真核生物系统中的研究不仅发现了由RNA-蛋白质结合介导的基因表达调控的机理,而且鉴定出结合RNA的蛋白家族中存在有共同的短段(Common motifs)。本文拟对目前研究的饶有兴趣的5SRNA-结合蛋白复合物以及RNP-致序列进行阐述和讨论。     

固有无序蛋白与蛋白质相互作用位点残基特征分析

本文对固有无序蛋白(IDPs)与其他蛋白质相互作用位点残基特征进行了研究.首先在数据库中选出满足条件的109条IDPs蛋白质链及与其他配体蛋白形成的299个IDPs-蛋白质复合物,然后提取复合物中作为相互作用位点的IDPs-蛋白质残基.这109条IDPs链中共含有50 031个氨基酸残基,其中处于作用位点的残基有4 822个.通过分析发现,20种氨基酸在形成IDPs-蛋白质相互作用位点残基时具有不同的倾向性,根据形成作用位点残基的倾向性,20种氨基酸可分成三大类:倾向型氨基酸(ILE、LEU、ARG、PHE、TYR、MET、TRP)、中间型氨基酸(GLN、GLU、THR、LYS、VAL、ASP、HIS)、非倾向型氨基酸(PRO、SER、GLY、ALA、ASN、CYS).研究结果还进一步表明,不同氨基酸在有序区域与无序区域形成IDPs-蛋白质作用位点残基的倾向性不同.其中,氨基酸TRP、LEU、ILE、CYS在有序和无序区域形成作用位点残基的差异性尤为明显,而氨基酸GLU、PHE、HIS、ALA则基本没有多大差别.对IDPs-蛋白质相互作用位点残基理化特征进行分析发现:疏水性强、侧链净电荷量较少、极性较小、溶剂可及性表面积较大、侧链体积较大、极化率较大的氨基酸比较倾向于形成作用位点残基.主成分分析结果显示,残基的极化率、侧链体积和溶剂可及表面积对作用位点残基影响最大.     

蛋白质相互作用热点残基的预测北大核心CSCD

氨基酸突变扫描实验揭示了在蛋白质相互作用的结合过程中大部分的结合自由能是由极少数热点残基贡献的,通常定义结合自由能变化△△G≥2.0 kcal/mol的蛋白质残基为热点残基。热点残基对蛋白质相互作用具有重要意义。因此,如何有效进行热点残基的预测,仍然是一个研究课题。综合蛋白质氨基酸理化属性的加权疏水性、加权残基接触数、结构属性溶剂可接近面积和残基突出指数等特征,提出利用机器学习支持向量机算法来预测热点残基的方法。所提方法在丙氨酸热力学数据库数据和结合界面数据库选定的数据集上有很好的效果。在一定程度上对以后的研究发展有所帮助。     

蛋白质- 核酸对接方法研究进展

分子对接技术作为预测蛋白质-核酸复合物结构的有效方法,为研究在生物学过程中蛋白质-核酸的相互作用提供了重要的工具。本文首先分析了当前蛋白质-核酸对接研究中的主要困难,例如构象变化和核糖磷酸骨架的带电性问题。然后从构象搜索、打分函数、柔性策略三个方面比较和总结了蛋白质-核酸对接中主要的计算方法。最后回顾了蛋白质-核酸对接计算模型的应用,并对未来的工作进行了展望。     

对EcoRI作用于DNA的新认识

对ＥｃｏＲＩ作用于ＤＮＡ的新认识邹国林皮新春（武汉大学生物化学与生物物理学系,武汉４３００７２）关键词蛋白质与核酸相互作用ＥｃｏＲＩ模体蛋白质与核酸的相互作用是分子生物学研究的中心问题之一。当前以阐明ＤＮＡ结合蛋白的结构与蛋白质－ＤＮＡ复合物的结构为...     

基于氨基酸组分和位点保守信息识别蛋白质HEME结合残基

血红素是一种重要的、常用的配体,在电子传递、催化、信号转导和基因表达等方面发挥着重要作用,准确预测蛋白质与血红素相互作用的结合残基是结构生物信息学的主要挑战之一。本文下载整理了Biolip数据库中HEME配体与蛋白质结合的信息,统计分析了结合残基和非结合残基的氨基酸组分和位点保守性信息并将其作为预测特征参数,用Fisher-PSSM判别法识别HEME结合残基,计算结果表明优化特征参数的Fisher-PSSM判别法得到了较好的预测结果。     

Computational analysis of hydrogen bonds in protein-RNA complexes for interaction patterns

Structural analysis of protein-RNA complexes is labor-intensive, yet provides insight into the interaction patterns between a protein and RNA. As the number of protein-RNA complex structures reported has increased substantially in the last few years, a systematic method is required for automatically identifying interaction patterns. This paper presents a computational analysis of the hydrogen bonds in the most representative set of protein-RNA complexes. The analysis revealed several interesting interaction patterns. (1) While residues in the beta-sheets favored unpaired nucleotides, residues in the helices showed no preference and residues in turns favored paired nucleotides. (2) The backbone hydrogen bonds were more dominant than the base hydrogen bonds in the paired nucleotides, but the reverse was observed in the unpaired nucleotides. (3) The protein-RNA complexes contained more paired nucleotides than unpaired nucleotides, but the unpaired nucleotides were observed more frequently interacting with the proteins. And (4) Arg-U, Thr-A, Lys-A, and Asn-U were the most frequently observed pairs. The interaction patterns discovered from the analysis will provide us with useful information in predicting the structure of the RNA binding protein and the structure of the protein binding RNA.     

Do electrostatic interactions destabilize protein–nucleic acid binding?

The negatively charged phosphates of nucleic acids are often paired with positively charged residues upon binding proteins. It was thus counter-intuitive when previous Poisson-Boltzmann (PB) calculations gave positive energies from electrostatic interactions, meaning that they destabilize protein-nucleic acid binding. Our own PB calculations on protein-protein binding have shown that the sign and the magnitude of the electrostatic component are sensitive to the specification of the dielectric boundary in PB calculations. A popular choice for the boundary between the solute low dielectric and the solvent high dielectric is the molecular surface; an alternative is the van der Waals (vdW) surface. In line with results for protein-protein binding, in this article, we found that PB calculations with the molecular surface gave positive electrostatic interaction energies for two protein-RNA complexes, but the signs are reversed when the vdW surface was used. Therefore, whether destabilizing or stabilizing effects are predicted depends on the choice of the dielectric boundary. The two calculation protocols, however, yielded similar salt effects on the binding affinity. Effects of charge mutations differentiated the two calculation protocols; PB calculations with the vdW surface had smaller deviations overall from experimental data.     

Protein-RNA contacts at crystal packing surfaces

The crystal packing surfaces comprising protein-RNA interactions were analyzed for 50 RNA-protein crystal structures in the Protein Data Bank database. Protein-RNA crystal contacts, which represent nonspecific protein-RNA interfaces, were investigated for their amino acid propensities, hydrogen bond patterns, and backbone and side chain interactions. When compared to biologically relevant interactions, the protein-RNA crystal contacts exhibit similarities as well as differences with respect to the principles of protein-RNA interactions. Similar to what was observed at cognate protein-RNA interfaces, positively charged amino acids have high propensities at noncognate protein-RNA interfaces and preferentially form hydrogen bonds with RNA phosphate groups. In contrast, nonpolar residues are less frequently associated with noncognate interactions. These results highlight the important roles of both electrostatic and hydrogen bonding interactions, facilitated by positively charged amino acids, in mediating both specific and nonspecific protein-RNA interactions.     

Discovering the interaction propensities of amino acids and nucleotides from protein-RNA complexes

With the availability of many genome sequences, the mining of biological data is attracting much attention, most of it limited to the sequences of macromolecules. Sequence data are easy to analyze as they can be treated as strings of characters, whereas the structure of a macromolecule is much more complex. We developed a set of algorithms to analyze the structures of protein-RNA complexes at the atomic level and used them to analyze protein-RNA interactions using structural data on 51 protein-RNA complexes. The analysis revealed, among other things, that: (1) polar and charged amino acids have a strong tendency to interact with nucleotides, (2) arginine and asparagine tend to hydrogen bond with uracil, and (3) histidine favors uracil in water-mediated bonding with RNA. We analyzed a large set of structural data of protein-RNA complexes involving water-mediated hydrogen bonds as well as direct hydrogen bonds. The interaction patterns discovered from the analysis provide useful information for predicting the structure of RNA that binds proteins, and of proteins that bind RNA.     

Site-directed mutagenesis of the GTP-binding domain of beta-tubulin.

Tubulin binds guanine nucleotides with high affinity and specificity. GTP, an allosteric effector of microtubule assembly, requires Mg2+ for its interaction with beta-tubulin and binds as the MgGTP complex. In contrast, GDP binding does not require Mg2+. The structural basis for this difference is not understood but may be of fundamental importance for microtubule assembly. We investigated the interaction of beta-tubulin with guanine nucleotides using site-directed mutagenesis. Acidic amino acid residues have been shown to interact with nucleotide in numerous nucleotide-binding proteins. In this study, we mutated seven highly conserved aspartic acid residues and one highly conserved glutamic acid residue in the putative GTP-binding domain of beta-tubulin (N-terminal 300 amino acids) to asparagine and glutamine, respectively. The mutants were synthesized in vitro using rabbit reticulocyte lysates, and their affinities for nucleotide determined by an h.p.l.c.-based assay. Our results indicate that the mutations can be placed in six separate categories on the basis of their effects on nucleotide binding. These categories range from having no effect on nucleotide binding to a mutation that apparently abolishes nucleotide binding. One mutation at Asp224 reduced the affinity of beta-tubulin for GTP in the presence but not in the absence of Mg2+. The specific effect of this mutation on nucleotide binding is consistent with an interaction of this amino acid with the Mg2+ moiety of MgGTP. This residue is in a region sharing sequence homology with the putative Mg2+ site in myosin and other ATP-binding proteins. As a result, tubulin belongs to a distinct class of GTP-binding proteins which may be evolutionarily related to the ATP-binding proteins.     

Acinetobacter cyclohexanone monooxygenase: gene cloning and sequence determination.

The gene coding for cyclohexanone monooxygenase from Acinetobacter sp. strain NCIB 9871 was isolated by immunological screening methods. We located and determined the nucleotide sequence of the gene. The structural gene is 1,626 nucleotides long and codes for a polypeptide of 542 amino acids; 389 nucleotides 5' and 108 nucleotides 3' of the coding region are also reported. The complete amino acid sequence of the enzyme was derived by translation of the nucleotide sequence. From a comparison of the amino acid sequence with consensus sequences of nucleotide-binding folds, we identified a potential flavin-binding site at the NH2 terminus of the enzyme (residues 6 to 18) and a potential nicotinamide-binding site extending from residue 176 to residue 208 of the protein. An overproduction system for the gene to facilitate genetic manipulations was also constructed by using the tac promoter vector pKK223-3 in Escherichia coli.     

Dissecting the protein-RNA interface: the role of protein surface shapes and RNA secondary structures in protein-RNA recognition

Protein-RNA interactions are essential for many biological processes. However, the structural mechanisms underlying these interactions are not fully understood. Here, we analyzed the protein surface shape (dented, intermediate or protruded) and the RNA base pairing properties (paired or unpaired nucleotides) at the interfaces of 91 protein-RNA complexes derived from the Protein Data Bank. Dented protein surfaces prefer unpaired nucleotides to paired ones at the interface, and hydrogen bonds frequently occur between the protein backbone and RNA bases. In contrast, protruded protein surfaces do not show such a preference, rather, electrostatic interactions initiate the formation of hydrogen bonds between positively charged amino acids and RNA phosphate groups. Interestingly, in many protein-RNA complexes that interact via an RNA loop, an aspartic acid is favored at the interface. Moreover, in most of these complexes, nucleotide bases in the RNA loop are flipped out and form hydrogen bonds with the protein, which suggests that aspartic acid is important for RNA loop recognition through a base-flipping process. This study provides fundamental insights into the role of the shape of the protein surface and RNA secondary structures in mediating protein-RNA interactions.     

Identification of basic amino acids at the N-terminal end of the core protein that are crucial for hepatitis C virus infectivity

A major function of the hepatitis C virus (HCV) core protein is the interaction with genomic RNA to form the nucleocapsid, an essential component of the virus particle. Analyses to identify basic amino acid residues of HCV core protein, important for capsid assembly, were initially performed with a cell-free system, which did not indicate the importance of these residues for HCV infectivity. The development of a cell culture system for HCV (HCVcc) allows a more precise analysis of these core protein amino acids during the HCV life cycle. In the present study, we used a mutational analysis in the context of the HCVcc system to determine the role of the basic amino acid residues of the core protein in HCV infectivity. We focused our analysis on basic residues located in two clusters (cluster 1, amino acids [aa]6 to 23; cluster 2, aa 39 to 62) within the N-terminal 62 amino acids of the HCV core protein. Our data indicate that basic residues of the first cluster have little impact on replication and are dispensable for infectivity. Furthermore, only four basic amino acids residues of the second cluster (R50, K51, R59, and R62) were essential for the production of infectious viral particles. Mutation of these residues did not interfere with core protein subcellular localization, core protein-RNA interaction, or core protein oligomerization. Moreover, these mutations had no effect on core protein envelopment by intracellular membranes. Together, these data indicate that R50, K51, R59, and R62 residues play a major role in the formation of infectious viral particles at a post-nucleocapsid assembly step.     

PRI-Modeler: extracting RNA structural elements from PDB files of protein-RNA complexes

A complete understanding of protein and RNA structures and their interactions is important for determining the binding sites in protein-RNA complexes. Computational approaches exist for identifying secondary structural elements in proteins from atomic coordinates. However, similar methods have not been developed for RNA, due in part to the very limited structural data so far available. We have developed a set of algorithms for extracting and visualizing secondary and tertiary structures of RNA and for analyzing protein-RNA complexes. These algorithms have been implemented in a web-based program called PRI-Modeler (protein-RNA interaction modeler). Given one or more protein data bank files of protein-RNA complexes, PRI-Modeler analyzes the conformation of the RNA, calculates the hydrogen bond (H bond) and van der Waals interactions between amino acids and nucleotides, extracts secondary and tertiary RNA structure elements, and identifies the patterns of interactions between the proteins and RNAs. This paper presents PRI-Modeler and its application to the hydrogen bond and van der Waals interactions in the most representative set of protein-RNA complexes. The analysis reveals several interesting interaction patterns at various levels. The information provided by PRI-Modeler should prove useful for determining the binding sites in protein-RNA complexes. PRI-Modeler is accessible at http://wilab.inha.ac.kr/primodeler/, and supplementary materials are available in the analysis results section at http://wilab.inha.ac.kr/primodeler/.