The Use of Proton Chemical Shifts to Define the Solution Structure of a Dimeric Peptide

For flexible peptides, nuclear Overhauser Effects (NOE) experiments do not provide enough information to ensure a correct definition of their solution structure. The use of distance constraints, derived from the knowledge of proton chemical shifts, is developed to restrict the number of possible conformations. In the case of flexible molecules, randomization appears as an important factor of the correct estimation of the chemical shifts from the 3D structure. The refinement of the solution structure of the highly flexible AVP-like parallel dimer is described to illustrate this process.     

Three-Dimensional Protein Fold Determination from Backbone Amide Pseudocontact Shifts Generated by Lanthanide Tags at Multiple Sites

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Evaluation of Unrestrained Replica-Exchange Simulations Using Dynamic Walkers in Temperature Space for Protein Structure Refinement

A central problem of computational structural biology is the refinement of modeled protein structures taken from either comparative modeling or knowledge-based methods. Simulations are commonly used to achieve higher resolution of the structures at the all-atom level, yet methodologies that consistently yield accurate results remain elusive. In this work, we provide an assessment of an adaptive temperature-based replica exchange simulation method where the temperature clients dynamically walk in temperature space to enrich their population and exchanges near steep energetic barriers. This approach is compared to earlier work of applying the conventional method of static temperature clients to refine a dataset of conformational decoys. Our results show that, while an adaptive method has many theoretical advantages over a static distribution of client temperatures, only limited improvement was gained from this strategy in excursions of the downhill refinement regime leading to an increase in the fraction of native contacts. To illustrate the sampling differences between the two simulation methods, energy landscapes are presented along with their temperature client profiles.     

Editing of Multidimensional NMR Spectra of Partially Deuterated Proteins. Measurement of Amide Deuterium Isotope Effects on the Chemical Shifts of Protein Backbone Nuclei

Novel multidimensional NMR pulse sequences are presented for determination of amide deuterium isotope effects on the 13C chemical shifts of the backbone in proteins. The sequences edit heteronuclear triple resonance spectra into two subspectra according to whether a deuterium or a proton is attached to 15N for the pertinent correlations. The new experiments are demonstrated using 13C, 15N-labeled RAP 17-112 (N-terminal domain of 2-macroglobulin receptor associated protein).     

Ab-inito Quantum Mechanical Calculations of NMR Chemical Shifts in Nucleic Acids Constituents II Conformational Dependence of the lH and 13C Chemical Shifts in the Ribose

Abstract

The magnetic shielding constant of the different ¹³C and ¹³H nuclei of a deoxyribose are calculated for the C2′ endo and C3′ endo puckerings of the furanose ring as a function of the conformation about the C4′C5′ bond. For the carbons the calculated variations are of several ppm, the C3′ endo puckering corresponding in most cases to a larger shielding than the C2′ endo one. For the protons the calculated variations of chemical shifts are all smaller than 1.3 ppm, that is of the order of magnitude of the variation of the geometrical shielding produced on these protons by the other units of a DNA double helix, with a change of the overall structure of the helix. The computations carried out on the deoxyribose ?3′ and 5′ phosphates for several conformations of the phosphate group tend to show that the changes of conformation of the charged group of atoms produce chemical shift variations smaller than the two conformational parameters of the deoxyribose itself. The calculations carried out for a ribose do give the general features of the differences between the carbon and proton spectra of deoxynucleosides and nucleosides.

The comparison of the measured and calculated phosphorylation shifts tend to show that the counterion contributes significantly, for some nuclei of the deoxyribose, to the shifts measured. The calculated magnitude of this polarization effect on carbon shifts suggests a tentative qualitative interpretation of carbon spectra of the ribose part of DNA double helices.     

Determining Protein Complex Connectivity Using a Probabilistic Deletion Network Derived from Quantitative Proteomics

Protein complexes are key molecular machines executing a variety of essential cellular processes. Despite the availability of genome-wide protein-protein interaction studies, determining the connectivity between proteins within a complex remains a major challenge. Here we demonstrate a method that is able to predict the relationship of proteins within a stable protein complex. We employed a combination of computational approaches and a systematic collection of quantitative proteomics data from wild-type and deletion strain purifications to build a quantitative deletion-interaction network map and subsequently convert the resulting data into an interdependency-interaction model of a complex. We applied this approach to a data set generated from components of the Saccharomyces cerevisiae Rpd3 histone deacetylase complexes, which consists of two distinct small and large complexes that are held together by a module consisting of Rpd3, Sin3 and Ume1. The resulting representation reveals new protein-protein interactions and new submodule relationships, providing novel information for mapping the functional organization of a complex.     

An Empirical Correlation between Secondary Structure Content and Averaged Chemical Shifts in Proteins

It is shown that the averaged chemical shift (ACS) of a particular nucleus in the protein backbone empirically correlates well to its secondary structure content (SSC). Chemical shift values of more than 200 proteins obtained from the Biological Magnetic Resonance Bank are used to calculate ACS values, and the SSC is estimated from the corresponding three-dimensional coordinates obtained from the Protein Data Bank. ACS values of ¹H_α show the highest correlation to helical and sheet structure content (correlation coefficient of 0.80 and 0.75, respectively); ¹H_N exhibits less reliability (0.65 for both sheet and helix), whereas such correlations are poor for the heteronuclei. SSC estimated using this correlation shows a good agreement with the conventional chemical shift index-based approach for a set of proteins that only have chemical shift information but no NMR or x-ray determined three-dimensional structure. These results suggest that even chemical shifts averaged over the entire protein retain significant information about the secondary structure. Thus, the correlation between ACS and SSC can be used to estimate secondary structure content and to monitor large-scale secondary structural changes in protein, as in folding studies.     

Backbone Structure Confirmation and Side Chain Conformation Refinement of a Bradykinin Mimic BKM-824 by Comparing Calculated 1H, 13C and 19F Chemical Shifts with Experiment

Abstract

Calculated and experimental ¹H, ¹³C and ¹⁹F chemical shifts were compared in BKM-824, a cyclic bradykinin antagonist mimic, c[Ava¹-Igl²-Ser³-DF5F⁴-Oic⁵-Arg⁶] (Ava=5-amino- valeric acid, Igl=α-(2-indanyl)glycine, DF5F=pentafluorophenylalanine, Oic=(2S,3aS,7aS)- octahydroindole-2-carboxylic acid). The conformation of BKM-824 has been studied earlier by NMR spectroscopy (M. Miskolzie et al., J. Biomolec. Struct. Dyn. 17, 947–955 (2000)). All NMR structures have qualitatively the same backbone structure but there is considerable variation in the side chain conformations. We have carried out quantum mechanical optimization for three representative NMR structures at the B3LYP/6–31G* level, constraining the backbone dihedral angles at their NMR structure values, followed by NMR chemical shift calculations at the optimized structures with the 6–311G** basis set. There is an intramolecular hydrogen bond at Ser³ in the optimized structures.

The experimental ¹³C chemical shifts at five C^α positions as well as at the C^β, C^γ and Cδ position of Ava¹, which forms part of the backbone, are well reproduced by the calculations, confirming the NMR backbone structure. A comparison between the calculated and experimental H^β chemical shifts in Igl² shows that the dominant conformation at this residue is gauche. Changes of proton chemical shifts with the scan of the χ1 angle in DF5F⁴ suggest that χ1 ≈180°. The calculated ¹H and ¹³C chemical shifts are in good agreement with experiment at the rigid residue Oic⁵. None of the models gives accurate results for Arg⁶, presumably because of its positive charge. Our study indicates that calculated NMR shifts can be used as additional constraints in conjunction with NMR data to determine protein conformations. However, to be computationally effective, a database of chemical shifts in small peptide fragments should be precalculated.     

乳抗氧化肽的分离纯化与结构鉴定

本文检测了不同分子量范围的WPI(乳清分离蛋白)酶解物的抗氧化活性,结果表明各个组分显示出不同的抗氧化活性,其中分子量小于5 kDa的组分最强。采用凝胶过滤色谱对分子量小于5 kDa的WPI酶解物进行分离,抗氧化活性强的组分继续采用RP-HPLC进行纯化。通过MALDI-TOF-MS与氨基酸组成分析鉴定该活性肽为His-Ile-Arg。     

i3Drefine Software for Protein 3D Structure Refinement and Its Assessment in CASP10

Protein structure refinement refers to the process of improving the qualities of protein structures during structure modeling processes to bring them closer to their native states. Structure refinement has been drawing increasing attention in the community-wide Critical Assessment of techniques for Protein Structure prediction (CASP) experiments since its addition in 8^th CASP experiment. During the 9^th and recently concluded 10^th CASP experiments, a consistent growth in number of refinement targets and participating groups has been witnessed. Yet, protein structure refinement still remains a largely unsolved problem with majority of participating groups in CASP refinement category failed to consistently improve the quality of structures issued for refinement. In order to alleviate this need, we developed a completely automated and computationally efficient protein 3D structure refinement method, i3Drefine, based on an iterative and highly convergent energy minimization algorithm with a powerful all-atom composite physics and knowledge-based force fields and hydrogen bonding (HB) network optimization technique. In the recent community-wide blind experiment, CASP10, i3Drefine (as ‘MULTICOM-CONSTRUCT’) was ranked as the best method in the server section as per the official assessment of CASP10 experiment. Here we provide the community with free access to i3Drefine software and systematically analyse the performance of i3Drefine in strict blind mode on the refinement targets issued in CASP10 refinement category and compare with other state-of-the-art refinement methods participating in CASP10. Our analysis demonstrates that i3Drefine is only fully-automated server participating in CASP10 exhibiting consistent improvement over the initial structures in both global and local structural quality metrics. Executable version of i3Drefine is freely available at http://protein.rnet.missouri.edu/i3drefine/.     

青鳉鱼DBI基因全长cDNA的克隆与蛋白结构分析

地西泮结合抑制因子(diazepam binding inhibitor,DBI)具有抑制由葡萄糖诱导的胰岛素分泌、促进胆固醇跨线粒体膜转运和调节脂肪酸合成与代谢等多种生理功能。本研究使用反转录PCR结合RACE方法克隆了青鳉鱼(Oryzias latipes)的DBI基因全长cDNA序列。该序列全长592bp,包含长度为102bp的5'端非编码区(5'-UTR),长度为220bp的3'端非编码区(3'-UTR),和长度为270bp的开放阅读框,推测其编码89个氨基酸。同源性分析结果显示青鳉鱼DBI蛋白序列与大西洋鲑、鲤鱼、斜带石斑鱼、斑马鱼、非洲爪蟾、大鼠和人的同源性分别为82%、76%、76%、75%、72%、71%和70%,说明DBI基因在脊椎动物的进化过程中非常保守。同源建模显示青鳉DBI蛋白的4个α螺旋结构围成一个脂酰CoA结合口袋,与已测定果蝇DBI蛋白具有非常相似的三级结构。本研究结果为阐明脊椎动物在进化过程中DBI分子结构的演变规律及DBI在低等脊椎动物中的作用机理等提供了有意义的科学参考。     

Comparison of Protein Structures in Solution Using Local Conformations Derived from NMR Data: Application to Cytochrome c

Abstract

Structural comparisons of proteins in solution are often required to examine structure-functional relationships, study structural effects of mutations or distinguish between various forms of the same molecule under different conditions. A nuclear magnetic resonance (NMR) based probabilistic strategy is presented and used to study the structural differences between the two redox states of cytochrome C in solution. A probabilistic approach is employed to calculate the main chain conformations of horse ferro- and ferricytochrome C in solution, based on the published sequential d connectivity data. Conformational differences between the two oxidation states of horse cytochrome C in solution are found to be statistically significant. The largest changes in conformation are at residues Lys27, Thr28, Leu32, Gln42, Thr47, Tyr48, Thr49, Glu69, Lys72, Met80, Phe82, Ile85 and Lys86, all of which are close to the heme (within 14 Å of the heme iron in the high resolution Xray structure of tuna cytochrome c). We suggest that these conformational changes may modulate local dipole moments and hence influence the interactions of cytochrome C with its physiological redox partners during the electron transfer process. The oxidation state dependent conformational differences are found to be much greater in solution than in the crystalline state, and the solution and crystal structures differ significantly in regions close to the heme. These results suggest that the highly charged nature of cytochrome C makes this protein particularly sensitive to the ionic strength of its environment and leads to differences between crystal and solution structures in the same oxidation state. In such cases, crystal structures must be used with caution for modeling molecular interactions in vivo. More generally, this analysis indicates that the determination of accurate local conformations based on nmr data can provide useful information about structure-functional aspects of proteins in solution.     

Modelling and Refinement of the Crystal Structure of Nucleoprotamine from Gibbuta Divaricata

Abstract

The molecular structure of nucleoprotamine from Gibbula divaricata and its packing in oriented fibers has been modelled both to fit the X-ray diffraction pattern and to avoid steric compression. The representative model consists of 5₁ poly(dinucleotide) B-DNA helices with 5₁ poly(hexapeptide) chains associated with the major grooves. The prevailing peptide conformation is β, The four arginine residues present are hydrogen-bonded to DNA phosphates while neutral peptides protrude into the minor grooves of neighboring nucleoprotamine molecules which are packed 2.61 nm apart in a screw-disordered, quasi-hexagonal lattice. This model reconciles a number of earlier, apparently conflicting experimental results and explains the remarkable stability of nucleoprotamines.     

Simultaneous Determination of Protein Structure and Dynamics Using Cryo-Electron Microscopy

Cryo-electron microscopy is rapidly emerging as a powerful technique to determine the structures of complex macromolecular systems elusive to other techniques. Because many of these systems are highly dynamical, characterizing their movements is also a crucial step to unravel their biological functions. To achieve this goal, we report an integrative modeling approach to simultaneously determine structure and dynamics of macromolecular systems from cryo-electron microscopy density maps. By quantifying the level of noise in the data and dealing with their ensemble-averaged nature, this approach enables the integration of multiple sources of information to model ensembles of structures and infer their populations. We illustrate the method by characterizing structure and dynamics of the integral membrane receptor STRA6, thus providing insights into the mechanisms by which it interacts with retinol binding protein and translocates retinol across the membrane.     

Development and Validation of a Method for Profiling Post-Translational Modification Activities Using Protein Microarrays

Background

Post-translational modifications (PTMs) impact on the stability, cellular location, and function of a protein thereby achieving a greater functional diversity of the proteome. To fully appreciate how PTMs modulate signaling networks, proteome-wide studies are necessary. However, the evaluation of PTMs on a proteome-wide scale has proven to be technically difficult. To facilitate these analyses we have developed a protein microarray-based assay that is capable of profiling PTM activities in complex biological mixtures such as whole-cell extracts and pathological specimens.

Methodology/Principal Findings

In our assay, protein microarrays serve as a substrate platform for in vitro enzymatic reactions in which a recombinant ligase, or extracts prepared from whole cells or a pathological specimen is overlaid. The reactions include labeled modifiers (e.g., ubiquitin, SUMO1, or NEDD8), ATP regenerating system, and other required components (depending on the assay) that support the conjugation of the modifier. In this report, we apply this methodology to profile three molecularly complex PTMs (ubiquitylation, SUMOylation, and NEDDylation) using purified ligase enzymes and extracts prepared from cultured cell lines and pathological specimens. We further validate this approach by confirming the in vivo modification of several novel PTM substrates identified by our assay.

Conclusions/Significance

This methodology offers several advantages over currently used PTM detection methods including ease of use, rapidity, scale, and sample source diversity. Furthermore, by allowing for the intrinsic enzymatic activities of cell populations or pathological states to be directly compared, this methodology could have widespread applications for the study of PTMs in human diseases and has the potential to be directly applied to most, if not all, basic PTM research.     

QAUST: Protein Function Prediction Using Structure Similarity,Protein Interaction,and Functional Motifs

The number of available protein sequences in public databases is increasing exponentially. However, a significant percentage of these sequences lack functional annotation, which is essential for the understanding of how biological systems operate. Here, we propose a novel method, Quantitative Annotation of Unknown STructure (QAUST), to infer protein functions, specifically Gene Ontology (GO) terms and Enzyme Commission (EC) numbers. QAUST uses three sources of information: structure information encoded by global and local structure similarity search, biological network information inferred by protein–protein interaction data, and sequence information extracted from functionally discriminative sequence motifs. These three pieces of information are combined by consensus averaging to make the final prediction. Our approach has been tested on 500 protein targets from the Critical Assessment of Functional Annotation (CAFA) benchmark set. The results show that our method provides accurate functional annotation and outperforms other prediction methods based on sequence similarity search or threading. We further demonstrate that a previously unknown function of human tripartite motif-containing 22 (TRIM22) protein predicted by QAUST can be experimentally validated.     

水稻MicroRNA的预测及实验验证

根据已报道水稻pre-miRNA的序列与结构信息,利用支持向量机（support vector machine, SVM）方法在miRNA前体上预测成熟区,产生一个模型——mature-SVM.它预测水稻成熟区的敏感性和特异性分别为86.7% 和100%;然后,用这个模型对从水稻基因组中筛选出的46.501条pre-miRNA进行成熟链预测,此外再根据miRNA的作用原理用blast程序所进一步的筛选,得到了127条pre-miRNA及成熟miRNA;除去其中已知的21条,最后得到106条候选的新的水稻miRNA. 从中随机挑取10条进行Northern验证,结果有4条miRNA得到确认.     

Prediction of Protein Secondary Structure Using Feature Selection and Analysis Approach

The prediction of the secondary structure of a protein from its amino acid sequence is an important step towards the prediction of its three-dimensional structure. However, the accuracy of ab initio secondary structure prediction from sequence is about 80 % currently, which is still far from satisfactory. In this study, we proposed a novel method that uses binomial distribution to optimize tetrapeptide structural words and increment of diversity with quadratic discriminant to perform prediction for protein three-state secondary structure. A benchmark dataset including 2,640 proteins with sequence identity of less than 25 % was used to train and test the proposed method. The results indicate that overall accuracy of 87.8 % was achieved in secondary structure prediction by using ten-fold cross-validation. Moreover, the accuracy of predicted secondary structures ranges from 84 to 89 % at the level of residue. These results suggest that the feature selection technique can detect the optimized tetrapeptide structural words which affect the accuracy of predicted secondary structures.