Solution nuclear magnetic resonance structure of the GATase subunit and structural Basis of the interaction between GATase and ATPPase subunits in a two-subunit-type GMPS from methanocaldococcus jannaschii

The solution structure of the monomeric glutamine amidotransferase (GATase) subunit of the Methanocaldococcus janaschii (Mj) guanosine monophosphate synthetase (GMPS) has been determined using high-resolution nuclear magnetic resonance methods. Gel filtration chromatography and N-15 backbone relaxation studies have shown that the Mj GATase subunit is present in solution as a 21 kDa (188-residue) monomer. The ensemble of 20 lowest-energy structures showed root-mean-square deviations of 0.35 +/- 0.06 angstrom for backbone atoms and 0.8 +/- 0.06 angstrom for all heavy atoms. Furthermore, 99.4% of the backbone dihedral angles are present in the allowed region of the Ramachandran map, indicating the stereochemical quality of the structure. The core of the tertiary structure of the GATase is composed of a seven-stranded mixed beta-sheet that is fenced by five alpha-helices. The Mj GATase is similar in structure to the Pyrococcus horikoshi (Ph) GATase subunit. Nuclear magnetic resonance (NMR) chemical shift perturbations and changes in line width were monitored to identify residues on GATase that were responsible for interaction with magnesium and the ATPPase subunit, respectively. These interaction studies showed that a common surface exists for the metal ion binding as well as for the protein-protein interaction. The dissociation constant for the GATase-Mg2+ interaction has been found to be similar to 1 mM, which implies that interaction is very weak and falls in the fast chemical exchange regime. The GATase-ATPPase interaction, on the other hand, falls in the intermediate chemical exchange regime on the NMR time scale. The implication of this interaction in terms of the regulation of the GATase activity of holo GMPS is discussed.

CINCINNATA in Antirrhinum majus directly modulates genes involved in cytokinin and auxin signaling

Mutations in the CINCINNATA (CIN) gene in Antirrhinum majus and its orthologs in Arabidopsis result in crinkly leaves as a result of excess growth towards the leaf margin. CIN homologs code for TCP (TEOSINTE-BRANCHED 1, CYCLOIDEA, PROLIFERATING CELL FACTOR 1 AND 2) transcription factors and are expressed in a broad zone in a growing leaf distal to the proliferation zone where they accelerate cell maturation. Although a few TCP targets are known, the functional basis of CIN-mediated leaf morphogenesis remains unclear. We compared the global transcription profiles of wild-type and the cin mutant of A. majus to identify the targets of CIN. We cloned and studied the direct targets using RNA in situ hybridization, DNA-protein interaction, chromatin immunoprecipitation and reporter gene analysis. Many of the genes involved in the auxin and cytokinin signaling pathways showed altered expression in the cin mutant. Further, we showed that CIN binds to genomic regions and directly promotes the transcription of a cytokinin receptor homolog HISTIDINE KINASE 4 (AmHK4) and an IAA3/SHY2 (INDOLE-3-ACETIC ACID INDUCIBLE 3/SHORT HYPOCOTYL 2) homolog in A. majus. Our results suggest that CIN limits excess cell proliferation and maintains the flatness of the leaf surface by directly modulating the hormone pathways involved in patterning cell proliferation and differentiation during leaf growth. 10.1111/(ISSN)1469-8137

The Structure of the Holo-Acyl Carrier Protein of Leishmania major Displays a Remarkably Different Phosphopantetheinyl Transferase Binding Interface

The genome of Leishmania major encodes a type II fatty acid biosynthesis pathway for which no structural or biochemical information exists. Here, for the first time, we have characterized the central player of the pathway, the acyl carrier protein (LmACP), using nuclear magnetic resonance (NMR). Structurally, the LmACP molecule is similar to other type II ACPs, comprising a four-helix bundle, enclosing a hydrophobic core. Dissimilarities in sequence, however, exist in helix II (recognition helix) of the protein. The enzymatic conversion of apo-LmACP into the holo form using type I (Escherichia coli AcpS) and type II (Sfp type) phosphopantetheinyl transferases (PPTs) is relatively slow. Mutagenesis studies underscore the importance of the residues present at the protein protein interaction interface of LmACP in modulating the activity of PPTs. Interestingly, the cognate PPT for this ACP, the L. major 4'-phosphopantetheinyl transferase (LmPPT), does not show any enzymatic activity toward it, though it readily converts other type I and type II ACPs into their holo forms. NMR chemical shift perturbation studies suggest a moderately tight complex between LmACP and its cognate PPT, suggesting inhibition. We surmise that the unique surface of LmACP might have evolved to complement its cognate enzyme (LmPPT), possibly for the purpose of regulation.

Micro-systems for Optical Protein-Chip

Protein-Chip as micro-assays for the determination of protein interaction, the analysis, the identification and the purification of proteins has large potential applications. The Optical Protein-Chip is able to detect the multi-interaction of proteins and multi-bio-activities of molecules directly and simultaneously with no labeling. The chip is a small matrix on solid substrate containing multi-micro-area prepared by microfabrication with photolithography or soft lithography for surface patterning, and processed with surface modification which includes the physical, chemical, and bio-chemical modifications, etc. The ligand immobilization, such as protein immobilization, especially the oriented immobilization with low steric hindrance and high bio-specific binding activity between ligand and receptor is used to form a sensing surface. Each area of the pattern is corresponding to only one bioactivity. The interval between the areas is non-bioactive and optically extinctive. The affinity between proteins is used to realize non-labeling microassays for the determination of protein identification and protein interaction. The sampling of the chip is non-disturbing, performed with imaging ellipsometry and image processing on a database of proteins.

Structural study of CUG-repeating small RNAs complexed with silencing suppressor P19

The study is focused on structural aspects of interaction between silencing suppressor p19 and CUG-repeating small RNAs. The work involves crystal structure determination of a protein-unbound RNA form and RNA fragments of various lengths (19, 20, 21 nucleotides) complexed with p19-suppressor. Results prove the ability of silencing suppressor p19 to bind CUG-repeating small RNAs, as well as reveal features of U•U mismatches flanked by Watson-Crick C•G base pairs in p19-bound and p19-unbound states. In addition, structural data reveal a p19 specific site for anchoring extra nucleotides in small RNAs. In general, the study extends our knowledge about the mechanism of small RNA recognition by silencing suppressor p19.

Chemical studies of viral entry mechanisms: I. Hydrophobic protein-lipid interactions during sendai virus membrane fusion. II. Kinetics of bacteriophage λ DNA injection.

Viruses possess very specific methods of targeting and entering cells. These methods would be extremely useful if they could also be applied to drug delivery, but little is known about the molecular mechanisms of the viral entry process. In order to gain further insight into mechanisms of viral entry, chemical and spectroscopic studies in two systems were conducted, examining hydrophobic protein-lipid interactions during Sendai virus membrane fusion, and the kinetics of bacteriophage λ DNA injection.

Sendai virus glycoprotein interactions with target membranes during the early stages of fusion were examined using time-resolved hydrophobic photoaffinity labeling with the lipid-soluble carbene generator3-(trifluoromethyl)-3-(m-^(125 )I] iodophenyl)diazirine (TID). The probe was incorporated in target membranes prior to virus addition and photolysis. During Sendai virus fusion with liposomes composed of cardiolipin (CL) or phosphatidylserine (PS), the viral fusion (F) protein is preferentially labeled at early time points, supporting the hypothesis that hydrophobic interaction of the fusion peptide at the N-terminus of the F_1 subunit with the target membrane is an initiating event in fusion. Correlation of the hydrophobic interactions with independently monitored fusion kinetics further supports this conclusion. Separation of proteins after labeling shows that the F_1 subunit, containing the putative hydrophobic fusion sequence, is exclusively labeled, and that the F_2 subunit does not participate in fusion. Labeling shows temperature and pH dependence consistent with a need for protein conformational mobility and fusion at neutral pH. Higher amounts of labeling during fusion with CL vesicles than during virus-PS vesicle fusion reflects membrane packing regulation of peptide insertion into target membranes. Labeling of the viral hemagglutinin/neuraminidase (HN) at low pH indicates that HN-mediated fusion is triggered by hydrophobic interactions, after titration of acidic amino acids. HN labeling under nonfusogenic conditions reveals that viral binding may involve hydrophobic as well as electrostatic interactions. Controls for diffusional labeling exclude a major contribution from this source. Labeling during reconstituted Sendai virus envelope-liposome fusion shows that functional reconstitution involves protein retention of the ability to undergo hydrophobic interactions.

Examination of Sendai virus fusion with erythrocyte membranes indicates that hydrophobic interactions also trigger fusion between biological membranes, and that HN binding may involve hydrophobic interactions as well. Labeling of the erythrocyte membranes revealed close membrane association of spectrin, which may play a role in regulating membrane fusion. The data show that hydrophobic fusion protein interaction with both artificial and biological membranes is a triggering event in fusion. Correlation of these results with earlier studies of membrane hydration and fusion kinetics provides a more detailed view of the mechanism of fusion.

The kinetics of DNA injection by bacteriophage λ. into liposomes bearing reconstituted receptors were measured using fluorescence spectroscopy. LamB, the bacteriophage receptor, was extracted from bacteria and reconstituted into liposomes by detergent removal dialysis. The DNA binding fluorophore ethidium bromide was encapsulated in the liposomes during dialysis. Enhanced fluorescence of ethidium bromide upon binding to injected DNA was monitored, and showed that injection is a rapid, one-step process. The bimolecular rate law, determined by the method of initial rates, revealed that injection occurs several times faster than indicated by earlier studies employing indirect assays.

It is hoped that these studies will increase the understanding of the mechanisms of virus entry into cells, and to facilitate the development of virus-mimetic drug delivery strategies.

白皮松花粉管发育过程中RNA、蛋白质和多糖类物质的合成及其动态变化

花粉管是有花植物受精过程中雄性生殖单位的载体，它同根毛、真菌菌丝一样，具有典型的极性顶端生长模式。裸子植物花粉与被子植物相比，具有萌发时间较长，生长缓慢等特点。但是目前人们对于裸子植物花粉萌发和花粉管生长的机理还不清楚。本文以裸子植物白皮松（Pinus bungeana）的花粉为材料，采用细胞学和生理生化方法，包括应用普通光学显微镜、荧光显微镜、激光扫描共聚焦显微镜、显微红外光谱（FTIR）和透射电镜（TEM）等技术，对其花粉萌发和花粉管生长过程进行了较为系统的研究，旨在进一步揭示裸子植物花粉管发育的调控机制。 本论文首先研究了外源Ca2+ 和3种调钙药物（A23187、EGTA、TMB8）对白皮松花粉萌发和花粉管生长的影响。结果表明，在离体培养条件下，高浓度的Ca2+（1%）能完全抑制白皮松花粉的萌发，低浓度的Ca2+ 则影响不大，而花粉萌发和花粉管生长的最适Ca2+ 浓度为0.01%。用Ca2+ 载体A23187、Ca2+ 螯合剂EGTA和钙通道阻滞剂TMB8分别处理花粉后，花粉萌发和花粉管生长均受到抑制。另外，用 Ca2+ 荧光探针 Fluo-3AM标记，对Ca2+ 的分布变化进行了观察，发现在花粉萌发的初期，Ca2+ 向萌发孔聚集。在正常生长的花粉管中Ca2+ 呈梯度分布，顶端荧光最强。与对照相比，A23187处理后花粉粒中荧光增强，而EGTA和TMB8处理的花粉粒中荧光强度均减弱。并且这3种调钙药物还破坏了花粉管顶端的Ca2+ 浓度梯度，最终导致花粉管的生长受阻。 花粉萌发和花粉管的生长依赖于RNA和蛋白质的不断合成。在放线菌素D的存在下，花粉萌发基本不受影响，但花粉管的生长速度下降，花粉管中RNA含量也减少。而经过放线菌酮处理后，花粉萌发和花粉管生长均受到抑制，花粉管中蛋白质含量降低，同时花粉管顶端显著膨大。通过SDS-PAGE的结果表明，花粉粒萌发前后蛋白质图谱有明显差异。FTIR光谱分析表明，两种抑制剂处理均导致花粉管壁的化学组成发生了变化，例如蛋白质和饱和酯含量减少，而羧酸的含量增加。此外，由放线菌酮和放线菌素D处理后，花粉管的超微结构也发生了明显变化，其中特别是花粉管顶端的分泌系统遭到严重破坏。 纤维素的正常合成对于白皮松花粉管的生长是必需的。在正常培养基中添加纤维素生物合成抑制剂2，6-二氯苯腈（DCB）后，花粉萌发几乎不受影响，但是花粉管的形态发生异常，生长速率降低。DCB处理还导致花粉管壁中纤维素含量下降，而胼胝质在花粉管顶端积累。用识别酯化果胶的JIM7和识别酸性果胶的JIM5对离体培养的白皮松花粉管进行标记后，发现果胶成分呈异常分布图式。FTIR光谱分析结果表明花粉管细胞壁中蛋白质、羧酸以及饱和酯含量增加。同时，在电镜下观察发现，花粉管细胞壁顶端呈现不均匀加厚，其中主要的细胞器，如高尔基体和线粒体等膜结构均遭到破坏。 上述结果说明，白皮松成熟花粉粒中已含有花粉萌发和花粉管早期生长所必需的Ca2+ 和RNA，但是在花粉管的后续伸长过程中仍需要外源Ca2+ 的参与以及新RNA、蛋白质的不断合成。与被子植物不同，裸子植物花粉萌发的启动也需要新蛋白的合成。尽管在花粉管中纤维素的含量很低，但是对于细胞壁的构建、花粉管的正常形态的维持起着关键作用。

DnaJ-like protein gene sll1384 is involved in phototaxis in Synechocystis sp PCC 6803

In Synechocystis sp. PCC 6803, gene sll1384 encodes a protein with a DnaJ domain at its N-terminal portion and a TPR domain at the C-terminal portion. An sll1384 mutant shows no difference from the wild type in adaptation to different temperatures, but almost completely loses its capability of phototactic movement. After complementation with sll1384, the mutant regains the phototaxis. As shown with electron microscopy, on the cell surface, mutant cells have pili that appear to be the same as that of the wild type. Also, the transformation efficiency remains unchanged in the mutant. It is postulated that Sll1384 regulates phototaxis of Synechocystis through protein-protein interaction. It is the first DnaJ-like protein gene identified in a cyanobacterium for a role in phototaxis.

Recent advances in the study of biomolecular interactions by capillary electrophoresis

Capillary electrophoresis (CE) has been abundantly used in the study of molecular interactions owing to such advantages as short analysis time, low sample size requirement, high separation efficiency, and flexible applications. The focus of this paper is to 2 review recent studies and advances (mainly from 1998 to now) in biomolecular interactions using CE. Five CE modes: zone migration CE, affinity CE, frontal analysis (FA), Hummel-Dreyer (HD) and vacancy peak (VP) are cited and compared. Quantitative aspects of the thermodynamics and kinetics of biomolecular interaction are reviewed. Several biomolecular binding systems, including protein-protein (polypeptide), protein-DNA (RNA), protein(polypeptide)-carbohydrate, protein-small molecule, DNA-small molecule, small molecule-small molecule, have been well characterized by CE. CE is shown to be a powerful tool for the determination of the binding parameters of various bioaffinity interactions.

Study of competitive binding of enantiomers to protein by affinity capillary electrochromatography

Affinity capillary electrochromatography (CEC) with zonal elution method was used to probe the competitive interactions of enantiomers with protein. In this approach, a known concentration of a competing agent is continuously applied to a CEC column with bovine serum albumin (BSA) physically adsorbed on SAX packing while injections of a small amount of analyte are made. The binding sites of solutes on the BSA molecule were determined by the changes in the retention factors of the solutes resulted from the addition of competitive agent. By using D- or L-tryptophan as competitive agents and D-, L-tryptophan and benzoin enantiomers as injected analytes showed that BSA molecule has a primary site to strongly bind L-tryptophan, but D-tryptophan dose not bind at this site; D- and L-tryptophan share a weak binding site on the BSA molecule. Benzoin enantiomers do not share any binding sites with either D- or L-tryptophan. Non-chiral compounds of trichloroacetic acid and n-hexanoic acid were applied as the competitive agents to study the binding of warfarin enantiomers to BSA, it was observed that trichloroacetic acid and n-hexanoic acid had a same binding site for warfarin enantiomers binding to BSA molecule. (C) 2002 Elsevier Science B.V. All rights reserved.

Uncovering the rules for protein-protein interactions from yeast genomic data

Identifying protein-protein interactions is crucial for understanding cellular functions. Genomic data provides opportunities and challenges in identifying these interactions. We uncover the rules for predicting protein-protein interactions using a frequent pattern tree (FPT) approach modified to generate a minimum set of rules (mFPT), with rule attributes constructed from the interaction features of the yeast genomic data. The mFPT prediction accuracy is benchmarked against other commonly used methods such as Bayesian networks and logistic regressions under various statistical measures. Our study indicates that mFPT outranks other methods in predicting the protein-protein interactions for the database used. We predict a new protein-protein interaction complex whose biological function is related to premRNA splicing and new protein-protein interactions within existing complexes based on the rules generated.

Electrostatic assembly of protein lysozyme on DNA visualized by atomic force microscopy

In the present work, atomic force microscopy (AFM) has been used to study the assembly of protein lysozyme on DNA molecule. Based on the electrostatic interaction, the positively charged lysozyme can easily bind onto the negatively charged DNA molecule surface. The protein molecules appear as globular objects on the DNA scaffold, which are distinguishable in the AFM images. At the same time, lysozyme molecules can be assembled onto DNA as dense or sporadic pattern by varying the protein concentration. This work may provide fundamental aspects for building protein nanostructures and studying of DNA-protein interaction.

Refining near-native protein-protein docking decoys by local resampling and energy minimization

How to refine a near-native structure to make it closer to its native conformation is an unsolved problem in protein-structure and protein-protein complex-structure prediction. In this article, we first test several scoring functions for selecting locally resampled near-native protein-protein docking conformations and then propose a computationally efficient protocol for structure refinement via local resampling and energy minimization. The proposed method employs a statistical energy function based on a Distance-scaled Ideal-gas REference state (DFIRE) as an initial filter and an empirical energy function EMPIRE (EMpirical Protein-InteRaction Energy) for optimization and re-ranking. Significant improvement of final top-1 ranked structures over initial near-native structures is observed in the ZDOCK 2.3 decoy set for Benchmark 1.0 (74% whose global rmsd reduced by 0.5 angstrom or more and only 7% increased by 0.5 angstrom or more). Less significant improvement is observed for Benchmark 2.0 (38% versus 33%). Possible reasons are discussed.

Integration of relational and hierarchical network information for protein function prediction

BACKGROUND:In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO) database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions.RESULTS:We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing.CONCLUSION:A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor) and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased positive predictive value), and that this increase is consistent uniformly with GO-term depth. Additional in silico validation on a collection of new annotations recently added to GO confirms the advantages suggested by the cross-validation study. Taken as a whole, our results show that a hierarchical approach to network-based protein function prediction, that exploits the ontological structure of protein annotation databases in a principled manner, can offer substantial advantages over the successive application of 'flat' network-based methods.

Computational Methods for RNA Structure Validation and Improvement.

With increasing recognition of the roles RNA molecules and RNA/protein complexes play in an unexpected variety of biological processes, understanding of RNA structure-function relationships is of high current importance. To make clean biological interpretations from three-dimensional structures, it is imperative to have high-quality, accurate RNA crystal structures available, and the community has thoroughly embraced that goal. However, due to the many degrees of freedom inherent in RNA structure (especially for the backbone), it is a significant challenge to succeed in building accurate experimental models for RNA structures. This chapter describes the tools and techniques our research group and our collaborators have developed over the years to help RNA structural biologists both evaluate and achieve better accuracy. Expert analysis of large, high-resolution, quality-conscious RNA datasets provides the fundamental information that enables automated methods for robust and efficient error diagnosis in validating RNA structures at all resolutions. The even more crucial goal of correcting the diagnosed outliers has steadily developed toward highly effective, computationally based techniques. Automation enables solving complex issues in large RNA structures, but cannot circumvent the need for thoughtful examination of local details, and so we also provide some guidance for interpreting and acting on the results of current structure validation for RNA.