A systematic approach to the comparison of protein structures

A systematic method has been developed for comparing the backbone conformations of proteins (Remington & Matthews, 1978). Two proteins are compared by successively optimizing the agreement between all possible segments of a chosen length from one protein, and all possible segments of the same length from the other protein. The method reveals any similarities between the two proteins, and provides an estimate of the statistical significance of any given structure agreement that is obtained.The method has been tested in a number of cases, including comparisons of the dehydrogenases and of the pancreatic and bacterial serine proteases. These examples were chosen to test the ability of the comparison method to detect structural similarities in the presence of large insertions and deletions. The results suggest that the detection of the “nucleotide binding fold” in the dehydrogenases is at the limit of the capability of the comparison technique in its original form, although it may be possible to generalize the method to allow for insertions and deletions in proteins.The results of many protein comparisons, made with different probe lengths, are summarized. For medium and long probe lengths, the average value of the structural agreement does not depend very much on the type of protein being compared. The average value of the structure agreement increases with the square root of the probe length, but for probe lengths above about 40 residues, the standard deviation is independent of probe length. From these observations it is possible to construct a generalized probability diagram to evaluate the significance of any structure agreement that might be obtained in comparing two proteins.     

A systematic approach to the large-scale production of protein crystals

Crystallization has recently emerged as a suitable process for the manufacture of biocatalysts in the form of cross-linked enzyme crystals (CLECs) or for the recovery of proteins from fermentation broths. In both instances it is essential to define conditions which control crystal size and habit, and that yield a reliable recovery of the active protein. Experiments to define the crystallization conditions usually depend on a factorial design (either incomplete or sparse matrix) or reverse screening techniques. In this work, we describe a simple procedure that allows the effect of three factors, for example protein concentration, precipitant concentration and pH, to be varied simultaneously and smoothly over a wide range. The results are mapped onto a simple triangular diagram where a 'window of crystallization' is immediately apparent, and that conveniently describes variations either in the crystal features, such as their yield, size, and habit, or in the recovery of biological activity. The approach is illustrated with two enzymes, yeast alcohol dehydrogenase (ADH I) and Candida rugosa lipase. For ADH the formation of two crystal habits (rod and hexagonal) could be controlled as a function of pH (6.5-10) and temperature (4-25 degrees C). At pH 7, in 10 to 16% w/v polyethylene glycol (PEG) 4000, only rod-shaped crystals formed whereas at pH 8, in 10 to 14% w/v PEG, only hexagonal crystals existed. For both enzymes, catalyst recovery was greatest at high crystallization agent concentrations and low protein concentration. For ADH, the greatest activity recovery was 87% whereas for the lipase crystals, by using 45% v/v 2-methyl-2,4-pentanediol (MPD) as the crystallization agent, a crystal recovery of 250 crystals per μl was obtained. For the lipase system, the use of crystal seeding was also shown to increase the crystal recovery by up to a factor of four. From the crystallization windows, the original conditions based on literature precedent (35% v/v MPD, 1 mM CaCl(2), 1.8 mg protein/ml) were altered (47.5% v/v MPD, 2 mM CaCl(2), 3 mg protein/ml). This led to an improved recovery of the lipase under conditions that scale reliably from 0.5 ml to 500 ml with no change in size, shape or recovery of the crystals themselves. Finally, these crystals were crosslinked with 5% v/v glutaraldehyde and mass and activity balances were calculated for the entire process of CLEC production. Up to 35% of the lipase activity present in the crude solid was finally recovered in the lipase CLECs after propan-2-ol fractionation, crystallization, and crosslinking.     

A probability-based approach for high-throughput protein phosphorylation analysis and site localization

Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) (Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%.     

A systematic comparative and structural analysis of protein phosphorylation sites based on the mtcPTM database

mtcPTM is an online repository of human and mouse phosphosites in which data are hierarchically organized to preserve biologically relevant experimental information, thus allowing straightforward comparisons of phosphorylation patterns found under different conditions. The database also contains the largest available collection of atomic models of phosphorylatable proteins. Detailed analysis of this structural dataset reveals that phosphorylation sites are found in a heterogeneous range of structural and sequence contexts. mtcPTM is available on the web .     

Characterization of protein kinase A phosphorylation: multi-technique approach to phosphate mapping

A multi-technique approach to identification and mapping of phosphorylation on protein kinase A (PKA) is described. X-ray crystallography revealed phosphorylation at T197 and S338 while mass spectrometry (MS) on the intact protein suggested phosphorylation at three sites. Tryptic digestion, followed by MS, confirmed the presence of three phosphates. However, metal affinity treatment of the digest prior to MS revealed the presence of a fourth phosphopeptide. Subsequent analysis of the digests using liquid chromatography (LC) coupled with quadrupole ion trap (QIT) MS confirmed phosphorylation at S10 and S338 and suggested phosphorylation at S139 and T195/197. Unfortunately, identification of pS139 was inconclusive due to low signal intensity and early elution in reversed-phase LC while poor MS/MS data prevented localization of the phosphate to T195 or T197. Phosphopeptide modification with ethanethiol, followed by LC QIT-MS/MS, identified four phosphopeptides in a single experiment. In addition, the fragmentation data provided significantly more sequence information than data obtained from unmodified peptides. Data from this study suggested that PKA was completely phosphorylated at S10, T197, and S338 and partially phosphorylated at S139. These results illustrate that critical information can be lost unless multiple MS techniques are used for identification and validation of phosphorylation.     

Phos-tag-based approach to study protein phosphorylation in the thylakoid membrane

Protein phosphorylation is a fundamental post-translational modification in all organisms. In photoautotrophic organisms, protein phosphorylation is essential for the fine-tuning of photosynthesis. The reversible phosphorylation of the photosystem II (PSII) core and the light-harvesting complex of PSII (LHCII) contribute to the regulation of photosynthetic activities. Besides the phosphorylation of these major proteins, recent phosphoproteomic analyses have revealed that several proteins are phosphorylated in the thylakoid membrane. In this study, we utilized the Phos-tag technology for a comprehensive assessment of protein phosphorylation in the thylakoid membrane of Arabidopsis. Phos-tag SDS-PAGE enables the mobility shift of phosphorylated proteins compared with their non-phosphorylated isoform, thus differentiating phosphorylated proteins from their non-phosphorylated isoforms. We extrapolated this technique to two-dimensional (2D) SDS-PAGE for detecting protein phosphorylation in the thylakoid membrane. Thylakoid proteins were separated in the first dimension by conventional SDS-PAGE and in the second dimension by Phos-tag SDS-PAGE. In addition to the isolation of major phosphorylated photosynthesis-related proteins, 2D Phos-tag SDS-PAGE enabled the detection of several minor phosphorylated proteins in the thylakoid membrane. The analysis of the thylakoid kinase mutants demonstrated that light-dependent protein phosphorylation was mainly restricted to the phosphorylation of the PSII core and LHCII proteins. Furthermore, we assessed the phosphorylation states of the structural domains of the thylakoid membrane, grana core, grana margin, and stroma lamella. Overall, these results demonstrated that Phos-tag SDS-PAGE is a useful biochemical tool for studying in vivo protein phosphorylation in the thylakoid membrane protein.

     

An approach to the systematic analysis of urinary steroids

1. Human urine, its extracts, extracts of urine pretreated with enzyme preparations containing β-glucuronidase and steroid sulphatase or β-glucuronidase alone, and products derived from the specific solvolysis of urinary steroid sulphates, were submitted to the following sequence of operations: reduction with borohydride; oxidation with a glycol-cleaving agent (bismuthate or periodate); separation of the products into ketones and others; oxidation of each fraction with tert.-butyl chromate, resolution of the end products by means of paper chromatography or gas–liquid chromatography or both. 2. Qualitative experiments indicated the kind of information the method and some of its modifications can provide. Quantitative experiments were restricted to the direct treatment of urine by the basic procedure outlined. It was partly shown and partly argued that the quantitative results were probably as informative about the composition of the major neutral urinary steroids (and certainly about their presumptive secretory precursors) as those obtained by a number of established analytical procedures. 3. A possible extension of the scope of the reported method was indicated. 4. A simple technique was introduced for the quantitative deposition of a solid sample on to a gas–liquid-chromatographic column.     

An approach to systematic detection of protein structural motifs

A procedure to detect similar local structures of proteins fromC coordinates is presented. First, the conformations of seven-residuepeptide segments are approximated by a limited number of representatives,each of which is assigned a symbol. Thus, the overall conformationof a protein is represented by a symbol string. The comparisonof these symbol strings using a sequence alignment techniquethen gives pairs of similar local structures. These pairs areconsidered candidates of structural motifs. The applicationof the procedure to the analysis of 93 proteins gave 858 pairsof similar local structures, which included several well-knownstructural motifs such as the nucleotide-binding ßß-unitand the calcium-binding EF hand. The characterization of aminoacid patterns of similar local structures given by the procedureshould be useful for the development of protein structure predictionbased on the acquisition of empirical rules from a large-scaledatabase.     

A systematic approach to biochemical profiling

Sequencing of the Arabidopsis thaliana genome is complete. The analytical tools for determining gene function by altering and monitoring gene expression are relatively well developed, and are generating large volumes of valuable data. Recent advances in techniques for the analysis of small molecules allow researchers to apply biochemical profiling as another powerful approach to functional genomics and metabolic research.     

Advances in the analysis of protein phosphorylation

Phosphorylation is one of the most relevant and ubiquitous post-translational modifications. Despite its relevance, the analysis of protein phosphorylation has been revealed as one of the most challenging tasks due to its highly dynamic nature and low stoichiometry. However, the development and introduction of new analytical methods are modifying rapidly and substantially this field. Especially important has been the introduction of more sensitive and specific methods for phosphoprotein and phosphopeptide purification as well as the use of more sensitive and accurate MS-based analytical methods. The integration of both approaches has enabled large-scale phosphoproteome studies to be performed, an unimaginable task few years ago. Additionally, methods originally developed for differential proteomics have been adapted making the study of the highly dynamic nature of protein phosphorylation feasible. This review aims at offering an overview on the most frequently used methods in phosphoprotein and phosphopeptide enrichment as well as on the most recent MS-based analysis strategies. Current strategies for quantitative phosphoproteomics and the study of the dynamics of protein phosphorylation are highlighted.     

A contact map matching approach to protein structure similarity analysis

We modeled the problem of identifying how close two proteins are structurally by measuring the dissimilarity of their contact maps. These contact maps are colored images, in which the chromatic information encodes the chemical nature of the contacts. We studied two conceptually distinct image-processing algorithms to measure the dissimilarity between these contact maps; one was a content-based image retrieval method, and the other was based on image registration. In experiments with contact maps constructed from the protein data bank, our approach was able to identify, with greater than 80% precision, instances of monomers of apolipoproteins, globins, plastocyanins, retinol binding proteins and thioredoxins, among the monomers of Protein Data Bank Select. The image registration approach was only slightly more accurate than the content-based image retrieval approach.     

A systematic analysis of protein palmitoylation in Caenorhabditis elegans

Background

Palmitoylation is a reversible post-translational protein modification which involves the addition of palmitate to cysteine residues. Palmitoylation is catalysed by the DHHC family of palmitoyl-acyl transferases (PATs) and reversibility is conferred by palmitoyl-protein thioesterases (PPTs). Mutations in genes encoding both classes of enzymes are associated with human diseases, notably neurological disorders, underlining their importance. Despite the pivotal role of yeast studies in discovering PATs, palmitoylation has not been studied in the key animal model Caenorhabditis elegans.

Results

Analysis of the C. elegans genome identified fifteen PATs, using the DHHC cysteine-rich domain, and two PPTs, by homology. The twelve uncategorised PATs were officially named using a dhhc-x system. Genomic data on these palmitoylation enzymes and those in yeast, Drosophila and humans was collated and analysed to predict properties and relationships in C. elegans. All available C. elegans strains containing a mutation in a palmitoylation enzyme were analysed and a complete library of RNA interference (RNAi) feeding plasmids against PAT or PPT genes was generated. To test for possible redundancy, double RNAi was performed against selected closely related PATs and both PPTs. Animals were screened for phenotypes including size, longevity and sensory and motor neuronal functions. Although some significant differences were observed with individual mutants or RNAi treatment, in general there was little impact on these phenotypes, suggesting that genetic buffering exists within the palmitoylation network in worms.

Conclusions

This study reports the first characterisation of palmitoylation in C. elegans using both in silico and in vivo approaches, and opens up this key model organism for further detailed study of palmitoylation in future.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-841) contains supplementary material, which is available to authorized users.     

A support vector machine approach to the identification of phosphorylation sites

We describe a bioinformatics tool that can be used to predict the position of phosphorylation sites in proteins based only on sequence information. The method uses the support vector machine (SVM) statistical learning theory. The statistical models for phosphorylation by various types of kinases are built using a dataset of short (9-amino acid long) sequence fragments. The sequence segments are dissected around post-translationally modified sites of proteins that are on the current release of the Swiss-Prot database, and that were experimentally confirmed to be phosphorylated by any kinase. We represent them as vectors in a multidimensional abstract space of short sequence fragments. The prediction method is as follows. First, a given query protein sequence is dissected into overlapping short segments. All the fragments are then projected into the multidimensional space of sequence fragments via a collection of different representations. Those points are classified with pre-built statistical models (the SVM method with linear, polynomial and radial kernel functions) either as phosphorylated or inactive ones. The resulting list of plausible sites for phosphorylation by various types of kinases in the query protein is returned to the user. The efficiency of the method for each type of phosphorylation is estimated using leave-one-out tests and presented here. The sensitivities of the models can reach over 70%, depending on the type of kinase. The additional information from profile representations of short sequence fragments helps in gaining a higher degree of accuracy in some phosphorylation types. The further development of an automatic phosphorylation site annotation predictor based on our algorithm should yield a significant improvement when using statistical algorithms in order to quantify the results.     

A systematic approach to dynamic programming in bioinformatics

MOTIVATION: Dynamic programming is probably the most popular programming method in bioinformatics. Sequence comparison, gene recognition, RNA structure prediction and hundreds of other problems are solved by ever new variants of dynamic programming. Currently, the development of a successful dynamic programming algorithm is a matter of experience, talent and luck. The typical matrix recurrence relations that make up a dynamic programming algorithm are intricate to construct, and difficult to implement reliably. No general problem independent guidance is available. RESULTS: This article introduces a systematic method for constructing dynamic programming solutions to problems in biosequence analysis. By a conceptual splitting of the algorithm into a recognition and an evaluation phase, algorithm development is simplified considerably, and correct recurrences can be derived systematically. Without additional effort, the method produces an early, executable prototype expressed in a functional programming language. The method is quite generally applicable, and, while programming effort decreases, no overhead in terms of ultimate program efficiency is incurred.     

Machine learning approach to predict protein phosphorylation sites by incorporating evolutionary information

Background  

Most of the existing in silico phosphorylation site prediction systems use machine learning approach that requires preparing a good set of classification data in order to build the classification knowledge. Furthermore, phosphorylation is catalyzed by kinase enzymes and hence the kinase information of the phosphorylated sites has been used as major classification data in most of the existing systems. Since the number of kinase annotations in protein sequences is far less than that of the proteins being sequenced to date, the prediction systems that use the information found from the small clique of kinase annotated proteins can not be considered as completely perfect for predicting outside the clique. Hence the systems are certainly not generalized. In this paper, a novel generalized prediction system, PPRED (Phosphorylation PREDictor) is proposed that ignores the kinase information and only uses the evolutionary information of proteins for classifying phosphorylation sites.