Structure Prediction Tools Research Articles

Surface Immunolabeling and Consensus Computational Framework To Identify Candidate Rare Outer Membrane Proteins ofTreponema pallidum

Treponema pallidum reacts poorly with the antibodies present in rabbit and human syphilitic sera, a property attributed to the paucity of proteins in its outer membrane. To better understand the basis for the syphilis spirochete's "stealth pathogenicity," we used a dual-label, 3-step amplified assay in which treponemes encapsulated in gel microdroplets were probed with syphilitic sera in parallel with anti-FlaA antibodies. A small (approximately 5 to 10%) but reproducible fraction of intact treponemes bound IgG and/or IgM antibodies. Three lines of evidence supported the notion that the surface antigens were likely β-barrel-forming outer membrane proteins (OMPs): (i) surface labeling with anti-lipoidal (VDRL) antibodies was not observed, (ii) immunoblot analysis confirmed prior results showing that T. pallidum glycolipids are not immunoreactive, and (iii) labeling of intact organisms was not appreciably affected by proteinase K (PK) treatment. With this method, we also demonstrate that TprK (TP0897), an extensively studied candidate OMP, and TP0136, a lipoprotein recently reported to be surface exposed, are both periplasmic. Consistent with the immunolabeling studies, TprK was also found to lack amphiphilicity, a characteristic property of β-barrel-forming proteins. Using a consensus computational framework that combined subcellular localization and β-barrel structural prediction tools, we generated ranked groups of candidate rare OMPs, the predicted T. pallidum outer membrane proteome (OMPeome), which we postulate includes the surface-exposed molecules detected by our enhanced gel microdroplet assay. In addition to underscoring the syphilis spirochete's remarkably poor surface antigenicity, our findings help to explain the complex and shifting balance between pathogen and host defenses that characterizes syphilitic infection.

MPlot--a server to analyze and visualize tertiary structure contacts and geometrical features of helical membrane proteins

MPlot is a webserver that provides a quick and easy way for structural biologists to analyze, visualize and plot tertiary structure contacts of helical membrane proteins. As input, experimentally determined or computationally modeled protein structures in PDB format are required. The automatic analysis concatenates in house tools to calculate cut-off dependent van der Waals contacts or crossing angles of transmembrane helices with third party tools to compute main chain or side chain hydrogen bonds or membrane planes. Moreover, MPlot allows new features and tools to be added on a regular basis. For that purpose, MPlot was embedded in a framework that facilitates advanced users to compose new workflows from existing tools, or to substitute intermediate results with results from their (own) tools. The outputs can be viewed online in a Jmol based protein viewer, or via automatically generated scripts in PyMOL. For further illustration, the results can be downloaded as a 2D graph, representing the spatial arrangement of transmembrane helices true to scale. For analysis and statistics, all results can be downloaded as text files that may serve as inputs for or as standard data to validate the output of knowledge based tertiary structure prediction tools.URL: http://proteinformatics.charite.de/mplot/.

GST profile expression study in some selected plants: in silico approach

Glutathione acts as a protein disulphide reductant, which detoxifies herbicides by conjugation, either spontaneously or by the activity of one of a number of glutathione-S-transferases (GSTs), and regulates gene expression in response to environmental stress and pathogen attack. GSTs play roles in both normal cellular metabolisms as well as in the detoxification of a wide variety of xenobiotic compounds, and they have been intensively studied with regard to herbicide detoxification in plants. A newly discovered plant GST subclass has been implicated in numerous stress responses, including those arising from pathogen attack, oxidative stress and heavy-metal toxicity. In addition, plants GSTs play a role in the cellular response to auxins and during the normal metabolism of plant secondary products like anthocyanins and cinnamic acid. The present work involves two in silico analytical approaches-general secondary structure prediction studies of the proteins and detailed signature pattern studies of some selected GST classes in Arabdiopsis thaliana, mustard, maize and bread wheat by standard Bioinformatics tools; structure prediction tools; signature pattern tools; and the evolutionary trends were analyzed by ClustalW. For this purpose, sequences were obtained from standard databases. The work reveals that these proteins are mainly alpha helical in nature with specific signature pattern similar to phosphokinase C, tyrosine kinase and casein kinase II proteins, which are closely related to plant oxidative stress. This study aims to comprehend the relationship of GST gene family and plant oxidative stress with respect to certain specific conserved motifs, which may help in future studies for screening of biomodulators involved in plant stress metabolism.

PSiFR: an integrated resource for prediction of protein structure and function

In the post-genomic era, the annotation of protein function facilitates the understanding of various biological processes. To extend the range of function annotation methods to the twilight zone of sequence identity, we have developed approaches that exploit both protein tertiary structure and/or protein sequence evolutionary relationships. To serve the scientific community, we have integrated the structure prediction tools, TASSER, TASSER-Lite and METATASSER, and the functional inference tools, FINDSITE, a structure-based algorithm for binding site prediction, Gene Ontology molecular function inference and ligand screening, EFICAz(2), a sequence-based approach to enzyme function inference and DBD-hunter, an algorithm for predicting DNA-binding proteins and associated DNA-binding residues, into a unified web resource, Protein Structure and Function prediction Resource (PSiFR). PSiFR is freely available for use on the web at http://psifr.cssb.biology.gatech.edu/

Beta-Barrel Hypothesis: Structural Insights to Oligomeric Prion Conformation

The denaturation of prion protein (PrP) and the concurrent formation of beta-sheet rich isoform has been accredited to the etiology of the prion diseases. Accumulating biochemical evidences underline the critical role of oligomeric PrP conformations emerging from the early stage of the denaturation process. However detailed structural information on the oligomeric isoforms remains elusive, which hampers precise description of the pathological process. Recently we proposed a new structural hypothesis for the oligomeric PrP species comprised of a short PrP construct (Human PrP 175-217) based on experimental findings. We postulated that 1) monomers adopt beta-hairpin conformation and 2) assemble as beta-barrel quaternary structure. These assumptions provided a comprehensive explanation for the experimental findings suggesting beta-sheet rich structure including circular dichroism (CD) spectrum and Fourier transformed infra-red spectroscopy (FTIR) as well as the presence of disulfide bridge between CYS-179 and CYS-214. To be more specific, we constructed various beta-barrel models differing in number of monomers, inter-molecular hydrogen bond pattern and side-chains facing exterior of the barrel. Those models were refined extensively using a protein structure prediction tool (Rosetta). Structural energy profile of the predicted oligomer models was consistently lower than that of native like monomer or oligomers comprised of partially denatured monomers. Also the smallest stable oligomer was predicted to be an octamer, which is in good agreement with available mass spectrometric data. Finally, we discussed a possible generality between protein denaturation and amyloidogenesis problems in general, by comparing our model with a oligomeric assembly model for the pathological amyloid beta protein (Abeta).

Prediction of novel miRNAs and associated target genes in Glycine max

BackgroundSmall non-coding RNAs (21 to 24 nucleotides) regulate a number of developmental processes in plants and animals by silencing genes using multiple mechanisms. Among these, the most conserved classes are microRNAs (miRNAs) and small interfering RNAs (siRNAs), both of which are produced by RNase III-like enzymes called Dicers. Many plant miRNAs play critical roles in nutrient homeostasis, developmental processes, abiotic stress and pathogen responses. Currently, only 70 miRNA have been identified in soybean.MethodsWe utilized Illumina's SBS sequencing technology to generate high-quality small RNA (sRNA) data from four soybean (Glycine max) tissues, including root, seed, flower, and nodules, to expand the collection of currently known soybean miRNAs. We developed a bioinformatics pipeline using in-house scripts and publicly available structure prediction tools to differentiate the authentic mature miRNA sequences from other sRNAs and short RNA fragments represented in the public sequencing data.ResultsThe combined sequencing and bioinformatics analyses identified 129 miRNAs based on hairpin secondary structure features in the predicted precursors. Out of these, 42 miRNAs matched known miRNAs in soybean or other species, while 87 novel miRNAs were identified. We also predicted the putative target genes of all identified miRNAs with computational methods and verified the predicted cleavage sites in vivo for a subset of these targets using the 5' RACE method. Finally, we also studied the relationship between the abundance of miRNA and that of the respective target genes by comparison to Solexa cDNA sequencing data.ConclusionOur study significantly increased the number of miRNAs known to be expressed in soybean. The bioinformatics analysis provided insight on regulation patterns between the miRNAs and their predicted target genes expression. We also deposited the data in a soybean genome browser based on the UCSC Genome Browser architecture. Using the browser, we annotated the soybean data with miRNA sequences from four tissues and cDNA sequencing data. Overlaying these two datasets in the browser allows researchers to analyze the miRNA expression levels relative to that of the associated target genes. The browser can be accessed at http://digbio.missouri.edu/soybean_mirna/.

The Ligand-Free State of the TPP Riboswitch: A Partially Folded RNA Structure

Riboswitches are elements of mRNA that regulate gene expression by undergoing structural changes upon binding of small ligands. Although the structures of several riboswitches have been solved with their ligands bound, the ligand-free states of only a few riboswitches have been characterized. The ligand-free state is as important for the functionality of the riboswitch as the ligand-bound form, but the ligand-free state is often a partially folded structure of the RNA, with conformational heterogeneity that makes it particularly challenging to study. Here, we present models of the ligand-free state of a thiamine pyrophosphate riboswitch that are derived from a combination of complementary experimental and computational modeling approaches. We obtain a global picture of the molecule using small-angle X-ray scattering data and use an RNA structure modeling software, MC-Sym, to fit local structural details to these data on an atomic scale. We have used two different approaches to obtaining these models. Our first approach develops a model of the RNA from the structures of its constituent junction fragments in isolation. The second approach treats the RNA as a single entity, without bias from the structure of its individual constituents. We find that both approaches give similar models for the ligand-free form, but the ligand-bound models differ for the two approaches, and only the models from the second approach agree with the ligand-bound structure known previously from X-ray crystallography. Our models provide a picture of the conformational changes that may occur in the riboswitch upon binding of its ligand. Our results also demonstrate the power of combining experimental small-angle X-ray scattering data with theoretical structure prediction tools in the determination of RNA structures beyond riboswitches.

Uncover the conserved property underlying sequence‐distant and structure‐similar proteins

It is widely accepted that a protein's sequence determines its structure. The surprising finding that proteins of distant sequence can adopt similar 3D structures has raised interesting questions regarding underlying conserved properties that are essential for protein folding and stability. Uncovering the conserved properties may shed light on the folding mechanism of proteins and help with the development of computational tools for protein structure prediction. We compiled and analyzed a structure pair dataset of 66 high-resolution and low sequence identity (16-38%) soluble proteins. Structure deviation for each pair was confirmed by calculating its C(alpha) SiMax value and comparing its potential energy per residue. Analysis of favorable inter-residue interactions for each structure pair indicated that the average number of inter-residue interactions within each structure represents a conserved feature of homologous structures of distant sequence. Detailed comparison of individual types of interactions showed that the average number of either hydrophobic or hydrogen bonding interactions remains unchanged for each structure pair. These findings should be of help to improving the quality of homology models based on templates of low sequence identity, thus broadening the application of homology modeling techniques for protein studies.

Molecular Dynamisc Simulation of Polyelectrolites

We carried out simulations of a polymer chain using molecular dynamics algorythm. As a model we used a three-dimensional set monomers (electrically charged material points) connected with its nearest neighbours by harmonic potential. Additionally all pairs of segments interacts by the Lennard-Jones (LJ) and Coulomb forces. The aim of the simulation was to determine chain conformation and other basic properties like radius of gyration and moment of inertia for various polymer length and electric charge distribution.Presented model could be alternative tool for structure prediction to typically used ones based on AMBER 99 [1] or another advanced force field.

A Transferable Coarse Grain Non-bonded Interaction Model For Amino Acids.

The large quantity of protein sequences being generated from genomic data has greatly outpaced the throughput of experimental protein structure determining methods and consequently brought urgency to the need for accurate protein structure prediction tools. Reduced resolution, or coarse grained (CG) models, have become a mainstay in computational protein structure prediction perfoming among the best tools available. The quest for high quality generalized CG models presents an extremely challenging yet popular endeavor. To this point, a CG based interaction potential is presented here for the naturally occurring amino acids. In the present approach, three to four heavy atoms and associated hydrogens are condensed into a single CG site. The parameterization of the site-site interaction potential relies on experimental data thus providing a novel approach that is neither based on all-atom (AA) simulations nor experimental protein structural data. Specifically, intermolecular potentials, which are based on Lennard-Jones (LJ) style functional forms, are parameterized using thermodynamic data including surface tension and density. Using this approach, an amino acid potential dataset has been developed for use in modeling peptides and proteins. The potential is evaluated here by comparing the solvent accessible surface area (SASA) to AA representations and ranking of protein decoy data sets provided by Decoys 'R' Us. The model is shown to perform very well compared to other existing prediction models for these properties.

Comparing four different approaches for the determination of inter-residue interactions provides insight for the structure prediction of helical membrane proteins

Studying inter-residue interactions provides insight into the folding and stability of both soluble and membrane proteins and is essential for developing computational tools for protein structure prediction. As the first step, various approaches for elucidating such interactions within protein structures have been proposed and proven useful. Since different approaches may grasp different aspects of protein structural folds, it is of interest to systematically compare them. In this work, we applied four approaches for determining inter-residue interactions to the analysis of three distinct structure datasets of helical membrane proteins and compared their correlation to the three individual quality measures of structures in these datasets. These datasets included one of 35 structures of rhodopsin receptors and bacterial rhodopsins determined at various resolutions, one derived from the HOMEP benchmark dataset previously reported, and one comprising of 139 homology models. It was found that the correlation between the average number of inter-residue interactions obtained by applying the four approaches and the available structure quality measures varied quite significantly among them. The best correlation was achieved by the approach focusing exclusively on favorable inter-residue interactions. These results provide interesting insight for the development of objective quality measure for the structure prediction of helical membrane proteins.

Template‐free protein structure prediction and quality assessment with an all‐atom free‐energy model

Biophysical forcefields have contributed less than originally anticipated to recent progress in protein structure prediction. Here, we have investigated the selectivity of a recently developed all-atom free-energy forcefield for protein structure prediction and quality assessment (QA). Using a heuristic method, but excluding homology, we generated decoy-sets for all targets of the CASP7 protein structure prediction assessment with <150 amino acids. The decoys in each set were then ranked by energy in short relaxation simulations and the best low-energy cluster was submitted as a prediction. For four of nine template-free targets, this approach generated high-ranking predictions within the top 10 models submitted in CASP7 for the respective targets. For these targets, our de-novo predictions had an average GDT_S score of 42.81, significantly above the average of all groups. The refinement protocol has difficulty for oligomeric targets and when no near-native decoys are generated in the decoy library. For targets with high-quality decoy sets the refinement approach was highly selective. Motivated by this observation, we rescored all server submissions up to 200 amino acids using a similar refinement protocol, but using no clustering, in a QA exercise. We found an excellent correlation between the best server models and those with the lowest energy in the forcefield. The free-energy refinement protocol may thus be an efficient tool for relative QA and protein structure prediction.

Discovering cis-Regulatory RNAs in Shewanella Genomes by Support Vector Machines

An increasing number of cis-regulatory RNA elements have been found to regulate gene expression post-transcriptionally in various biological processes in bacterial systems. Effective computational tools for large-scale identification of novel regulatory RNAs are strongly desired to facilitate our exploration of gene regulation mechanisms and regulatory networks. We present a new computational program named RSSVM (RNA Sampler+Support Vector Machine), which employs Support Vector Machines (SVMs) for efficient identification of functional RNA motifs from random RNA secondary structures. RSSVM uses a set of distinctive features to represent the common RNA secondary structure and structural alignment predicted by RNA Sampler, a tool for accurate common RNA secondary structure prediction, and is trained with functional RNAs from a variety of bacterial RNA motif/gene families covering a wide range of sequence identities. When tested on a large number of known and random RNA motifs, RSSVM shows a significantly higher sensitivity than other leading RNA identification programs while maintaining the same false positive rate. RSSVM performs particularly well on sets with low sequence identities. The combination of RNA Sampler and RSSVM provides a new, fast, and efficient pipeline for large-scale discovery of regulatory RNA motifs. We applied RSSVM to multiple Shewanella genomes and identified putative regulatory RNA motifs in the 5′ untranslated regions (UTRs) in S. oneidensis, an important bacterial organism with extraordinary respiratory and metal reducing abilities and great potential for bioremediation and alternative energy generation. From 1002 sets of 5′-UTRs of orthologous operons, we identified 166 putative regulatory RNA motifs, including 17 of the 19 known RNA motifs from Rfam, an additional 21 RNA motifs that are supported by literature evidence, 72 RNA motifs overlapping predicted transcription terminators or attenuators, and other candidate regulatory RNA motifs. Our study provides a list of promising novel regulatory RNA motifs potentially involved in post-transcriptional gene regulation. Combined with the previous cis-regulatory DNA motif study in S. oneidensis, this genome-wide discovery of cis-regulatory RNA motifs may offer more comprehensive views of gene regulation at a different level in this organism. The RSSVM software, predictions, and analysis results on Shewanella genomes are available at http://ural.wustl.edu/resources.html#RSSVM.

A new cloning system using a mutant esterase containing MCS as an indicator for gene cloning

A new cloning vector, pTcp216M-MCS, containing an engineered esterase ESTL120P as an indicator was constructed for the screening of positive clones harboring recombinant plasmids. After cloning the mutant esterase gene into pTrc99A, a synthetic multiple cloning site (MCS) was inserted into the predicted gaps of the esterase ESTL120P. These gaps were selected based on the results of comparative analysis of a family of carboxylesterases that was conducted using multiple sequence alignments and a secondary structure prediction tool. The reliability and reproducibility of the resulting vector with the novel indicator to discriminate positive clones from negative ones were compared with those of pTGFP and pBluescript II SK+, which utilized a green fluorescent protein and β-galactosidase as an indicator, respectively. The results demonstrated that pTcp216M-MCS had a higher fidelity and indicating ability than other vectors, which suggested that the esterase could be used as a new indicator for gene cloning.

Protein structure prediction on the Web: a case study using the Phyre server

Determining the structure and function of a novel protein is a cornerstone of many aspects of modern biology. Over the past decades, a number of computational tools for structure prediction have been developed. It is critical that the biological community is aware of such tools and is able to interpret their results in an informed way. This protocol provides a guide to interpreting the output of structure prediction servers in general and one such tool in particular, the protein homology/analogy recognition engine (Phyre). New profile-profile matching algorithms have improved structure prediction considerably in recent years. Although the performance of Phyre is typical of many structure prediction systems using such algorithms, all these systems can reliably detect up to twice as many remote homologies as standard sequence-profile searching. Phyre is widely used by the biological community, with >150 submissions per day, and provides a simple interface to results. Phyre takes 30 min to predict the structure of a 250-residue protein.

CPSP-web-tools: a server for 3D lattice protein studies

Summary: Studies on proteins are often restricted to highly simplified models to face the immense computational complexity of the associated problems. Constraint-based protein structure prediction (CPSP) tools is a package of very fast algorithms for ab initio optimal structure prediction and related problems in 3D HP-models [cubic and face centered cubic (FCC)]. Here, we present CPSP-web-tools, an interactive online interface of these programs for their immediate use. They include the first method for the direct prediction of optimal energies and structures in 3D HP side-chain models. This newest extension of the CPSP approach is described here for the first time.Availability and Implementation: Free access at http://cpsp.informatik.uni-freiburg.deContact: cpsp@informatik.uni-freiburg.de; cpsp@informatik.uni-freiburg.de

Inter-residue interactions in protein structures exhibit power-law behavior

Inter-residue interactions play an essential role in driving protein folding, and analysis of these interactions increases our understanding of protein folding and stability and facilitates the development of tools for protein structure and function prediction. In this work, we systematically characterized the change of inter-residue interactions at various sequence separation cutoffs using two protein datasets. The first set included 100 diverse, nonredundant and high-resolution soluble protein structures, covering all four major structural classes, all-alpha, alpha/beta, alpha+beta, and all-beta; and the second set included 20 diverse, nonredundant and high-resolution membrane protein structures, representing 19 unique superfamilies. It was shown that the average number of inter-residue interactions in structures of both datasets displays the power-law behavior. Fitting parameters of the power-law function are directly related to the structural classes analyzed. These findings provided further insight into the distribution of short-, medium-, and long-range inter-residue interactions in both soluble and membrane proteins and could be used for protein structure prediction.

Comparison of predicted binders in Rhipicephalus (Boophilus) microplus intestine protein variants BM86 Campo Grande strain, BM86 and BM95

This paper reports the sequence analysis of Bm86 Campo Grande strain comparing it with Bm86 and Bm95 antigens from the preparations TickGardPLUS and Gavac, respectively. The PCR product was cloned into pMOSBlue and sequenced. The secondary structure prediction tool PSIPRED was used to calculate alpha helices and beta strand contents of the predicted polypeptide. The hydrophobicity profile was calculated using the algorithms from the Hopp and Woods method, in addition to identification of potential MHC class-I binding regions in the antigens. Pair-wise alignment revealed that the similarity between Bm86 Campo Grande strain and Bm86 is 0.2% higher than that between Bm86 Campo Grande strain and Bm95 antigens. The identities were 96.5% and 96.3% respectively. Major suggestive differences in hydrophobicity were predicted among the sequences in two specific regions.

ConStruct: Improved construction of RNA consensus structures

BackgroundAligning homologous non-coding RNAs (ncRNAs) correctly in terms of sequence and structure is an unresolved problem, due to both mathematical complexity and imperfect scoring functions. High quality alignments, however, are a prerequisite for most consensus structure prediction approaches, homology searches, and tools for phylogeny inference. Automatically created ncRNA alignments often need manual corrections, yet this manual refinement is tedious and error-prone.ResultsWe present an extended version of CONSTRUCT, a semi-automatic, graphical tool suitable for creating RNA alignments correct in terms of both consensus sequence and consensus structure. To this purpose CONSTRUCT combines sequence alignment, thermodynamic data and various measures of covariation.One important feature is that the user is guided during the alignment correction step by a consensus dotplot, which displays all thermodynamically optimal base pairs and the corresponding covariation. Once the initial alignment is corrected, optimal and suboptimal secondary structures as well as tertiary interaction can be predicted. We demonstrate CONSTRUCT's ability to guide the user in correcting an initial alignment, and show an example for optimal secondary consensus structure prediction on very hard to align SECIS elements. Moreover we use CONSTRUCT to predict tertiary interactions from sequences of the internal ribosome entry site of CrP-like viruses. In addition we show that alignments specifically designed for benchmarking can be easily be optimized using CONSTRUCT, although they share very little sequence identity.ConclusionCONSTRUCT's graphical interface allows for an easy alignment correction based on and guided by predicted and known structural constraints. It combines several algorithms for prediction of secondary consensus structure and even tertiary interactions. The CONSTRUCT package can be downloaded from the URL listed in the Availability and requirements section of this article.

Mutational analysis of betaCOP (Sec26p) identifies an appendage domain critical for function.

BackgroundThe appendage domain of the γCOP subunit of the COPI vesicle coat bears a striking structural resemblance to adaptin-family appendages despite limited primary sequence homology. Both the γCOP appendage domain and an equivalent region on βCOP contain the FxxxW motif; the conservation of this motif suggested the existence of a functional appendage domain in βCOP.ResultsSequence comparisons in combination with structural prediction tools show that the fold of the COOH-terminus of Sec26p is strongly predicted to closely mimic that of adaptin-family appendages. Deletion of the appendage domain of Sec26p results in inviability in yeast, over-expression of the deletion construct is dominant negative and mutagenesis of this region identifies residues critical for function. The ArfGAP Glo3p was identified via suppression screening as a potential downstream modulator of Sec26p in a manner that is independent of the GAP activity of Glo3p but requires the presence of the COOH-terminal ISS motifs.ConclusionTogether, these results indicate an essential function for the predicted βCOP appendage and suggest that both COPI appendages perform a biologically active regulatory role with a structure related to adaptin-family appendage domains.