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At least 343 records · Page 19Linked to original sources

PubMed2005

An engineered chaperonin caging a guest protein: Structural insights and potential as a protein expression tool.

The structure of a chaperonin caging a substrate protein is not quite clear. We made engineered group II chaperonins fused with a guest protein and analyzed their structural and functional features. Thermococcus sp. KS-1 chaperonin alpha-subunit (TCP) which forms an eightfold symmetric double-ring structure was used. Expression plasmids were constructed which carried two or four TCP genes ligated head to tail in phase and a target protein gene at the 3' end of the linked TCP genes. Electron microscopy showed that the expressed gene products with the molecular sizes of ~120 kDa (di-TCP) and ~230 kDa (tetra-TCP) formed double-ring complexes similar to those of wild-type TCP. The tetra-TCP retained ATPase activity and its thermostability was significantly higher than that of the wild type. A 260-kDa fusion protein of tetra-TCP and green fluorescent protein (GFP, 27 kDa) was able to form the double-ring complexes with green fluorescence. Image analyses indicated that the GFP moiety of tetra-TCP/GFP fusion protein was accommodated in the central cavity, and tetra-TCP/GFP formed the closed-form similar to that crystallographically resolved in group II chaperonins. Furthermore, it was suggested that caging GFP expanded the cavity around the bottom. Using this tetra-TCP fusion strategy, two virus structural proteins (21-25 kDa) toxic to host cells or two antibody fragments (25-36 kDa) prone to aggregate were well expressed in the soluble fraction of Escherichia coli. These fusion products also assembled to double-ring complexes, suggesting encapsulation of the guest proteins. The antibody fragments liberated by site-specific protease digestion exhibited ligand-binding activities.

Adenosine Triphosphatases↗

PubMed2006

Protein-structure prediction by recombination of fragments.

The field of protein-structure prediction has been revolutionized by the application of "mix-and-match" methods both in template-based homology modeling and in template-free de novo folding. Consensus analysis and recombination of fragments copied from known protein structures is currently the only approach that allows the building of models that are closer to the native structure of the target protein than the structure of its closest homologue. It is also the most successful approach in cases in which the target protein exhibits a novel three-dimensional fold. This review summarizes the recent developments in both template-based and template-free protein structure modeling and compares the available methods for protein-structure prediction by recombination of fragments. A convergence between the "protein folding" and "protein evolution" schools of thought is postulated.

Peptide Fragments↗

PubMed2002

Use of structure comparison methods for the refinement of protein structure predictions. I. Identifying the structural family of a protein from low-resolution models.

Predicting the three-dimensional structure of proteins is still one of the most challenging problems in molecular biology. Despite its difficulty, several investigators have started to produce consistently low-resolution predictions for small proteins. However, in most of these cases, the prediction accuracy is still too low to make them useful. In the present article, we address the problem of obtaining better-quality predictions, starting from low-resolution models. To this end, we have devised a new procedure that uses these models, together with structure comparison methods, to identify the structural family of the target protein. This would allow, in a second step not described in the present work, to refine the predictions using conserved features of the identified family. In our approach, the structure database is investigated using predictions, at different accuracy levels, for a given protein. As query structures, we used both low-resolution versions of the native structures, as well as different sets of low accuracy predictions. In general, we found that for predictions with a resolution of > or =5-7 A, structure comparison methods were able to identify the fold of a protein in the top positions.

Databases, Protein↗

PubMed2004

Helix packing moments reveal diversity and conservation in membrane protein structure.

Helical membrane proteins are more tightly packed and the packing interactions are more diverse than those found in helical soluble proteins. Based on a linear correlation between amino acid packing values and interhelical propensity, we propose the concept of a helix packing moment to predict the orientation of helices in helical membrane proteins and membrane protein complexes. We show that the helix packing moment correlates with the helix interfaces of helix dimers of single pass membrane proteins of known structure. Helix packing moments are also shown to help identify the packing interfaces in membrane proteins with multiple transmembrane helices, where a single helix can have multiple contact surfaces. Analyses are described on class A G protein-coupled receptors (GPCRs) with seven transmembrane helices. We show that the helix packing moments are conserved across the class A family of GPCRs and correspond to key structural contacts in rhodopsin. These contacts are distinct from the highly conserved signature motifs of GPCRs and have not previously been recognized. The specific amino acid types involved in these contacts, however, are not necessarily conserved between subfamilies of GPCRs, indicating that the same protein architecture can be supported by a diverse set of interactions. In GPCRs, as well as membrane channels and transporters, amino acid residues with small side-chains (Gly, Ala, Ser, Cys) allow tight helix packing by mediating strong van der Waals interactions between helices. Closely packed helices, in turn, facilitate interhelical hydrogen bonding of both weakly polar (Ser, Thr, Cys) and strongly polar (Asn, Gln, Glu, Asp, His, Arg, Lys) amino acid residues. We propose the use of the helix packing moment as a complementary tool to the helical hydrophobic moment in the analysis of transmembrane sequences.

Hydrophobic and Hydrophilic Interactions↗

PubMed2003

Recognizing the fold of a protein structure.

This paper reports a graph-theoretic program, GRATH, that rapidly, and accurately, matches a novel structure against a library of domain structures to find the most similar ones. GRATH generates distributions of scores by comparing the novel domain against the different types of folds that have been classified previously in the CATH database of structural domains. GRATH uses a measure of similarity that details the geometric information, number of secondary structures and number of residues within secondary structures, that any two protein structures share. Although GRATH builds on well established approaches for secondary structure comparison, a novel scoring scheme has been introduced to allow ranking of any matches identified by the algorithm. More importantly, we have benchmarked the algorithm using a large dataset of 1702 non-redundant structures from the CATH database which have already been classified into fold groups, with manual validation. This has facilitated introduction of further constraints, optimization of parameters and identification of reliable thresholds for fold identification. Following these benchmarking trials, the correct fold can be identified with the top score with a frequency of 90%. It is identified within the ten most likely assignments with a frequency of 98%. GRATH has been implemented to use via a server (http://www.biochem.ucl.ac.uk/cgi-bin/cath/Grath.pl). GRATH's speed and accuracy means that it can be used as a reliable front-end filter for the more accurate, but computationally expensive, residue based structure comparison algorithm SSAP, currently used to classify domain structures in the CATH database. With an increasing number of structures being solved by the structural genomics initiatives, the GRATH server also provides an essential resource for determining whether newly determined structures are related to any known structures from which functional properties may be inferred.

Algorithms↗

PubMed2004

Nuclear localization of avian polyomavirus structural protein VP1 is a prerequisite for the formation of virus-like particles.

Virions of polyomaviruses consist of the major structural protein VP1, the minor structural proteins VP2 and VP3, and the viral genome associated with histones. An additional structural protein, VP4, is present in avian polyomavirus (APV) particles. As it had been reported that expression of APV VP1 in insect cells did not result in the formation of virus-like particles (VLP), the prerequisites for particle formation were analyzed. To this end, recombinant influenza viruses were created to (co)express the structural proteins of APV in chicken embryo cells, permissive for APV replication. VP1 expressed individually or coexpressed with VP4 did not result in VLP formation; both proteins (co)localized in the cytoplasm. Transport of VP1, or the VP1-VP4 complex, into the nucleus was facilitated by the coexpression of VP3 and resulted in the formation of VLP. Accordingly, a mutant APV VP1 carrying the N-terminal nuclear localization signal of simian virus 40 VP1 was transported to the nucleus and assembled into VLP. These results support a model of APV capsid assembly in which complexes of the structural proteins VP1, VP3 (or VP2), and VP4, formed within the cytoplasm, are transported to the nucleus using the nuclear localization signal of VP3 (or VP2); there, capsid formation is induced by the nuclear environment.

Amino Acid Sequence↗

PubMed1987

Structural proteins of bovine parainfluenza-3 virus.

Six structural proteins of bovine parainfluenza-3 virus (PI-3V) labeled with [35S]-methionine could be resolved by polyacrylamide gel electrophoresis (PAGE). Five structural proteins of this virus had been previously reported. The 6 proteins found in this study were: L, a 180,000 (180 kD) molecular weight (MW) large protein; P, 83 kD phosphoprotein; HN, 69 kD hemagglutinin-neuraminidase glycoprotein; NP, 66 kD nucleocapsid protein; F, 55 kD fusion glycoprotein; and M, 38 kD matrix protein. Selective labeling with [2-3H]-mannose revealed only HN and F glycoprotein bands. A cellular actin protein (43 kD), associated with many enveloped viruses, was also found as a seventh protein in bovine PI-3V.

Animals↗

PubMed2006

A method for localizing ligand binding pockets in protein structures.

The accurate identification of ligand binding sites in protein structures can be valuable in determining protein function. Once the binding site is known, it becomes easier to perform in silico and experimental procedures that may allow the ligand type and the protein function to be determined. For example, binding pocket shape analysis relies heavily on the correct localization of the ligand binding site. We have developed SURFNET-ConSurf, a modular, two-stage method for identifying the location and shape of potential ligand binding pockets in protein structures. In the first stage, the SURFNET program identifies clefts in the protein surface that are potential binding sites. In the second stage, these clefts are trimmed in size by cutting away regions distant from highly conserved residues, as defined by the ConSurf-HSSP database. The largest clefts that remain tend to be those where ligands bind. To test the approach, we analyzed a nonredundant set of 244 protein structures from the PDB and found that SURFNET-ConSurf identifies a ligand binding pocket in 75% of them. The trimming procedure reduces the original cleft volumes by 30% on average, while still encompassing an average 87% of the ligand volume. From the analysis of the results we conclude that for those cases in which the ligands are found in large, highly conserved clefts, the combined SURFNET-ConSurf method gives pockets that are a better match to the ligand shape and location. We also show that this approach works better for enzymes than for nonenzyme proteins.

Algorithms↗

PubMed1995

Prediction of protein structural classes.

A protein is usually classified into one of the following five structural classes: alpha, beta, alpha + beta, alpha/beta, and zeta (irregular). The structural class of a protein is correlated with its amino acid composition. However, given the amino acid composition of a protein, how may one predict its structural class? Various efforts have been made in addressing this problem. This review addresses the progress in this field, with the focus on the state of the art, which is featured by a novel prediction algorithm and a recently developed database. The novel algorithm is characterized by a covariance matrix that takes into account the coupling effect among different amino acid components of a protein. The new database was established based on the requirement that the classes should have (1) as many nonhomologous structures as possible, (2) good quality structure, and (3) typical or distinguishable features for each of the structural classes concerned. The very high success rate for both the training-set proteins and the testing-set proteins, which has been further validated by a simulated analysis and a jackknife analysis, indicates that it is possible to predict the structural class of a protein according to its amino acid composition if an ideal and complete database can be established. It also suggests that the overall fold of a protein is basically determined by its amino acid composition.

Algorithms↗

PubMed1987

Purification and characterization of a proline-rich secretory protein that is a precursor to a structural protein of an insect spermatophore.

The spermatophore or sperm sac of Tenebrio molitor (yellow mealworm beetle) is an acellular structure composed mostly of structural proteins, termed spermatophorins. The proteins are derived from the bean-shaped accessory reproductive glands of the male and are assembled into the multilayered structure within the ejaculatory duct. Homogenates of the secretory plug from this gland were used as immunogens for the production of monoclonal antibodies, including one identified as PL 21.1 which recognizes an antigen in the gland and the spermatophore. With the aid of gel filtration and immunoaffinity chromatography with a PL 21.1, we isolated a glandular secretory protein that is a precursor to a spermatophorin with similar electrophoretic mobility. On native polyacrylamide gels, the antigen from gland homogenates has an apparent molecular mass of 370 kDa. On sodium dodecyl sulfate gels, the antigen from the gland and that from the spermatophore have apparent molecular masses of 23 kDa. According to immunoblots of sodium dodecyl sulfate gels, the 23-kDa glandular antigen is organ-specific and adult-specific. By immunocytochemistry with PL 21.1, we found the antigens to be restricted to secretory vesicles of only one cell type in the gland and to a discrete layer in the outer wall of the spermatophore. The 23-kDa secretory antigen is distinguished by being high in glutamic acid/glutamine (15.4%) and in proline (25.2%).

Animals↗

PubMedDate not supplied

[Comparative analysis of the virion structural proteins of 3 nuclear polyhedrosis viruses].

The composition of structural proteins of virions of nuclear polyhedrosis viruses (NPV) of Barathra brassicae L., Lymantria dispor L. and Aporia crataegi L. was studied by polyacrylamide gel-SDS electrophoresis (PAGE-SDS). The object of the study included fractions of virion bundles in the envelope. All the baculoviruses under study were shown to have in virion structural proteins 23-24 polypeptides with molecular weights ranging from 12500 to 95000 daltons. Alongside with polypeptides of similar molecular weight, each baculovirus was shown to have a specific set of structural proteins allowing them to be readily identified. Specific distribution of major polypeptides of the virions was found. All the protein fractions were readily reproducible in repeated analyses with the exception of two minor polypeptides of NPV of Barathra brassicae L. The study showed that the composition of structural proteins of virions may be an important criterion for identification of baculoviruses under identical electrophoresis conditions.

Electrophoresis, Polyacrylamide Gel↗

PubMed2006

Advances in homology protein structure modeling.

Homology modeling plays a central role in determining protein structure in the structural genomics project. The importance of homology modeling has been steadily increasing because of the large gap that exists between the overwhelming number of available protein sequences and experimentally solved protein structures, and also, more importantly, because of the increasing reliability and accuracy of the method. In fact, a protein sequence with over 30% identity to a known structure can often be predicted with an accuracy equivalent to a low-resolution X-ray structure. The recent advances in homology modeling, especially in detecting distant homologues, aligning sequences with template structures, modeling of loops and side chains, as well as detecting errors in a model, have contributed to reliable prediction of protein structure, which was not possible even several years ago. The ongoing efforts in solving protein structures, which can be time-consuming and often difficult, will continue to spur the development of a host of new computational methods that can fill in the gap and further contribute to understanding the relationship between protein structure and function.

Animals↗

PubMed2006

PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics.

BACKGROUND: The number of protein structures from structural genomics centers dramatically increases in the Protein Data Bank (PDB). Many of these structures are functionally unannotated because they have no sequence similarity to proteins of known function. However, it is possible to successfully infer function using only structural similarity. RESULTS: Here we present the PDB-UF database, a web-accessible collection of predictions of enzymatic properties using structure-function relationship. The assignments were conducted for three-dimensional protein structures of unknown function that come from structural genomics initiatives. We show that 4 hypothetical proteins (with PDB accession codes: 1VH0, 1NS5, 1O6D, and 1TO0), for which standard BLAST tools such as PSI-BLAST or RPS-BLAST failed to assign any function, are probably methyltransferase enzymes. CONCLUSION: We suggest that the structure-based prediction of an EC number should be conducted having the different similarity score cutoff for different protein folds. Moreover, performing the annotation using two different algorithms can reduce the rate of false positive assignments. We believe, that the presented web-based repository will help to decrease the number of protein structures that have functions marked as "unknown" in the PDB file. AVAILABILITY: http://paradox.harvard.edu/PDB-UF and http://bioinfo.pl/PDB-UF.

Chromosome Mapping↗

PubMed2000

Protein structure modeling for structural genomics.

The shapes of most protein sequences will be modeled based on their similarity to experimentally determined protein structures. The current role, limitations, challenges and prospects for protein structure modeling (using information about genes and genomes) are discussed in the context of structural genomics.

Computer Simulation↗

PubMed2003

ModLoop: automated modeling of loops in protein structures.

SUMMARY: ModLoop is a web server for automated modeling of loops in protein structures. The input is the atomic coordinates of the protein structure in the Protein Data Bank format, and the specification of the starting and ending residues of one or more segments to be modeled, containing no more than 20 residues in total. The output is the coordinates of the non-hydrogen atoms in the modeled segments. A user provides the input to the server via a simple web interface, and receives the output by e-mail. The server relies on the loop modeling routine in MODELLER that predicts the loop conformations by satisfaction of spatial restraints, without relying on a database of known protein structures. For a rapid response, ModLoop runs on a cluster of Linux PC computers. AVAILABILITY: The server is freely accessible to academic users at http://salilab.org/modloop

Amino Acid Sequence↗

PubMed1992

Effective vaccination against papilloma development by immunization with L1 or L2 structural protein of cottontail rabbit papillomavirus.

Immunization of rabbits with either L1, the major structural protein, or L2, a minor structural protein of cottontail rabbit papillomavirus (CRPV), protected against challenge with the virus. Neutralizing antibodies were elicited by both the L1 and L2 trpE fusion proteins. Neutralization with anti-L1 serum, however, was more efficient than with anti-L2 serum. In contrast, when tested on Western blots the immune response to L2 was stronger than to L1. Rabbits were also protected against CRPV infection by immunization with L1 expressing recombinant vaccinia virus. Sera from two of three rabbits immunized with recombinant vaccinia virus were negative on Western blots but all three were positive in ELISA's with nondenatured fusion protein or in immunoprecipitations. The results suggest that both the viral structural proteins, L1 and L2, merit consideration in the development of a vaccine against papillomavirus.

Animals↗

PubMed2006

Servers for protein structure prediction.

The 1990s cultivated a generation of protein structure human predictors. As a result of structural genomics and genome sequencing projects, and significant improvements in the performance of protein structure prediction methods, a generation of automated servers has evolved in the past few years. Servers for close and distant homology modeling are now routinely used by many biologists, and have already been applied to the experimental structure determination process itself, and to the interpretation and annotation of genome sequences. Because dozens of servers are currently available, it is hard for a biologist to know which server(s) to use; however, the state of the art of these methods is now assessed through the LiveBench and CAFASP experiments. Meta-servers--servers that use the results of other autonomous servers to produce a consensus prediction--have proven to be the best performers, and are already challenging all but a handful of expert human predictors. The difference in performance of the top ten autonomous (non-meta) servers is small and hard to assess using relatively small test sets. Recent experiments suggest that servers will soon free humans from most of the burden of protein structure prediction.

Computational Biology↗

PubMed2003

LGA: A method for finding 3D similarities in protein structures.

We present the LGA (Local-Global Alignment) method, designed to facilitate the comparison of protein structures or fragments of protein structures in sequence dependent and sequence independent modes. The LGA structure alignment program is available as an online service at http://PredictionCenter.llnl.gov/local/lga. Data generated by LGA can be successfully used in a scoring function to rank the level of similarity between two structures and to allow structure classification when many proteins are being analyzed. LGA also allows the clustering of similar fragments of protein structures.

Algorithms↗