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Background: Automatic extraction of motifs from biological sequences is an important research problem in study of molecular biology. For proteins, it is desired to discover sequence motifs containing a large number of wildcard symbols, as the residues associated with functional sites are usually largely separated in sequences. Discovering such patterns is time-consuming because abundant combinations exist when long gaps (a gap consists of one or more successive wildcards) are considered. Mining algorithms often employ constraints to narrow down the search space in order to increase efficiency. However, improper constraint models might degrade the sensitivity and specificity of the motifs discovered by computational methods. We previously proposed a new constraint model to handle large wildcard regions for discovering functional motifs of proteins. The patterns that satisfy the proposed constraint model are called W-patterns. A W-pattern is a structured motif that groups motif symbols into pattern blocks interleaved with large irregular gaps. Considering large gaps reflects the fact that functional residues are not always from a single region of protein sequences, and restricting motif symbols into clusters corresponds to the observation that short motifs are frequently present within protein families. To efficiently discover W-patterns for large-scale sequence annotation and function prediction, this paper first formally introduces the problem to solve and proposes an algorithm named WildSpan (sequential pattern mining across large wildcard regions) that incorporates several pruning strategies to largely reduce the mining cost. Results: WildSpan is shown to efficiently find W-patterns containing conserved residues that are far separated in sequences. We conducted experiments with two mining strategies, protein-based and family-based mining, to evaluate the usefulness of W-patterns and performance of WildSpan. The protein-based mining mode of WildSpan is developed for discovering functional regions of a single protein by referring to a set of related sequences (e.g. its homologues). The discovered W-patterns are used to characterize the protein sequence and the results are compared with the conserved positions identified by multiple sequence alignment (MSA). The family-based mining mode of WildSpan is developed for extracting sequence signatures for a group of related proteins (e.g. a protein family) for protein function classification. In this situation, the discovered W-patterns are compared with PROSITE patterns as well as the patterns generated by three existing methods performing the similar task. Finally, analysis on execution time of running WildSpan reveals that the proposed pruning strategy is effective in improving the scalability of the proposed algorithm. Conclusions: The mining results conducted in this study reveal that WildSpan is efficient and effective in discovering functional signatures of proteins directly from sequences. The proposed pruning strategy is effective in improving the scalability of WildSpan. It is demonstrated in this study that the W-patterns discovered by WildSpan provides useful information in characterizing protein sequences. The WildSpan executable and open source codes are available on the web (http://biominer.csie.cyu.edu.tw/wildspan). [ABSTRACT FROM AUTHOR]

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that ‘leftover’ proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module allows cells to tune where endocytosis occurs, providing sensitive control over cargo uptake via clathrin-coated vesicles. [ABSTRACT FROM AUTHOR]

How cuticular proteins (CPs) interact with chitin and with each other in the cuticle remains unresolved. We employed LC-MS/MS to identify CPs from 5–6 day-old adults of Anopheles gambiae released after serial extraction with PBS, EDTA, 2-8M urea, and SDS as well as those that remained unextracted. Results were compared to published data on time of transcript abundance, localization of proteins within structures and within the cuticle, as well as properties of individual proteins, length, pI, percent histidine, tyrosine, glutamine, and number of AAP[A/V/L] repeats. Thirteen proteins were solubilized completely, all were CPRs, most belonging to the RR-1 group. Eleven CPs were identified in both soluble fractions and the final pellet, including 5 from other CP families. Forty-three were only detected from the final pellet. These included CPRs and members of the CPAP1, CPF, CPFL, CPLCA, CPLCG, CPLCP, and TWDL families, as well as several low complexity CPs, not assigned to families and named CPLX. For a given protein, many histidines or tyrosines or glutamines appear to be potential participants in cross-linking since we could not identify any peptide bearing these residues that was consistently absent. We failed to recover peptides from the amino-terminus of any CP. Whether this implicates that location in sclerotization or some modification that prevents detection is not known. Soluble CPRs had lower isoelectric points than those that remained in the final pellet; most members of other CP families had isoelectric points of 8 or higher. Obviously, techniques beyond analysis of differential solubility will be needed to learn how CPs interact with each other and with chitin. [ABSTRACT FROM AUTHOR]

Albumin fusion technology, the combination of small molecular proteins or peptides with human serum albumin (HSA), is an effective method for improving the medicinal values of natural small molecular proteins or peptides. However, comparative studies between HSA-fusion proteins or peptides and the parent small molecules in biological and molecular mechanisms are less reported. In this study, we examined the binding property of two novel somatostatin-HSA fusion proteins, (SST14)2-HSA and (SST28)2-HSA, to human SSTRs in stably expressing SSTR1-5 HEK 293 cells; observed the regulation of receptor internalization and internalized receptor recycling; and detected the receptors activation of HSA fusion proteins in stably expressing SSTR2- and SSTR3-EGFP cells. We showed that both somatostatin-HSA fusion proteins had high affinity to all five SSTRs, stimulated the ERK1/2 phosphorylation and persistently inhibited the accumulation of forskolin-stimulated cAMP in SSTR2- and SSTR3-expressing cells; but were less potent than the synthetic somatostatin-14 (SST-14). Our experiments also showed that somatostatin-HSA fusion proteins did not induce the receptors internalization; rather, they accelerated the recycling of the internalized receptors induced by SST-14 to the plasma membrane. Our results indicated that somatostatin-HSA fusion proteins, different from SST-14, exhibit some particular properties in binding, regulating, and activating somatostatin receptors. [ABSTRACT FROM AUTHOR]

The difficulty of maintaining intact protein complexes while minimizing non-specific background remains a significant limitation in proteomic studies. Labile interactions, such as the interaction between p120-catenin and the E-cadherin complex, are particularly challenging. Using the cadherin complex as a model-system, we have developed a procedure for efficient recovery of otherwise labile protein-protein interactions. We have named the procedure "ReCLIP" (Reversible Cross- Link Immuno-Precipitation) to reflect the primary elements of the method. Using cell-permeable, thiol-cleavable crosslinkers, normally labile interactions (i.e. p120 and E-cadherin) are stabilized in situ prior to isolation. After immunoprecipitation, crosslinked binding partners are selectively released and all other components of the procedure (i.e. beads, antibody, and p120 itself) are discarded. The end result is extremely efficient recovery with exceptionally low background. ReCLIP therefore appears to provide an excellent alternative to currently available affinity-purification approaches, particularly for studies of labile complexes. [ABSTRACT FROM AUTHOR]

Background: Conservation of the spatial binding organizations at the level of physico-chemical interactions is important for the formation and stability of protein-protein complexes as well as protein and drug design. Due to the lack of computational tools for recognition of spatial patterns of interactions shared by a set of protein-protein complexes, the conservation of such interactions has not been addressed previously. Results: We performed extensive spatial comparisons of physico-chemical interactions common to different types of protein-protein complexes. We observed that 80% of these interactions correspond to known hot spots. Moreover, we show that spatially conserved interactions allow prediction of hot spots with a success rate higher than obtained by methods based on sequence or backbone similarity. Detection of spatially conserved interaction patterns was performed by our novel MAPPIS algorithm. MAPPIS performs multiple alignments of the physico-chemical interactions and the binding properties in three dimensional space. It is independent of the overall similarity in the protein sequences, folds or amino acid identities. We present examples of interactions shared between complexes of colicins with immunity proteins, serine proteases with inhibitors and T-cell receptors with superantigens. We unravel previously overlooked similarities, such as the interactions shared by the structurally different RNase-inhibitor families. Conclusion: The key contribution of MAPPIS is in discovering the 3D patterns of physicochemical interactions. The detected patterns describe the conserved binding organizations that involve energetically important hot spot residues and are crucial for the protein-protein associations. [ABSTRACT FROM AUTHOR]

We focus on the problem of prediction with confidence and describe a recently developed learning algorithm called transductive confidence machine for making qualified region predictions. Its main advantage, in comparison with other classifiers, is that it is well-calibrated, with number of prediction errors strictly controlled by a given predefined confidence level. We apply the transductive confidence machine to the problems of acute leukaemia and ovarian cancer prediction using microarray and proteomics pattern diagnostics, respectively. We demonstrate that the algorithm performs well, yielding well-calibrated and informative predictions whilst maintaining a high level of accuracy. [ABSTRACT FROM AUTHOR]

The biological functions of a protein are closely related to its attributes in a cell. With the rapid accumulation of newly found protein sequence data in databanks, it is highly desirable to develop an automated method for predicting the subcellular location of proteins. The establishment of such a predictor will expedite the functional determination of newly found proteins and the process of prioritizing genes and proteins identified by genomic efforts as potential molecular targets for drug design. The traditional algorithms for predicting these attributes were based solely on amino acid composition in which no sequence order effect was taken into account. To improve the prediction quality, it is necessary to incorporate such an effect. However, the number of possible patterns in protein sequences is extremely large, posing a formidable difficulty for realizing this goal. To deal with such difficulty, a well-developed tool in digital signal processing named digital Fourier transform (DFT) [1] was introduced. After being translated to a digital signal according to the hydrophobicity of each amino acid, a protein was analyzed by DFT within the frequency domain. A set of frequency spectrum parameters, thus obtained, were regarded as the factors to represent the sequence order effect. A significant improvement in prediction quality was observed by incorporating the frequency spectrum parameters with the conventional amino acid composition. One of the crucial merits of this approach is that many existing tools in mathematics and engineering can be easily applied in the predicting process. It is anticipated that digital signal processing may serve as a useful vehicle for many other protein science areas. [ABSTRACT FROM AUTHOR]

Model-free analysis of NMR relaxation data, which is widely used for the study of protein dynamics, consists of the separation of the global rotational diffusion from internal motions relative to the diffusion frame and the description of these internal motions by amplitude and timescale. Five model-free models exist, each of which describes a different type of motion. Model-free analysis requires the selection of the model which best describes the dynamics of the NH bond. It will be demonstrated that the model selection technique currently used has two significant flaws, under-fitting, and not selecting a model when one ought to be selected. Under-fitting breaks the principle of parsimony causing bias in the final model-free results, visible as an overestimation of S2 and an underestimation of τe and Rex. As a consequence the protein falsely appears to be more rigid than it actually is. Model selection has been extensively developed in other fields. The techniques known as Akaike's Information Criteria (AIC), small sample size corrected AIC (AICc), Bayesian Information Criteria (BIC), bootstrap methods, and cross-validation will be compared to the currently used technique. To analyse the variety of techniques, synthetic noisy data covering all model-free motions was created. The data consists of two types of three-dimensional grid, the Rex grids covering single motions with chemical exchange {S2,τe,Rex}, and the Double Motion grids covering two internal motions {Sf2,Ss2,τs}. The conclusion of the comparison is that for accurate model-free results, AIC model selection is essential. As the method neither under, nor over-fits, AIC is the best tool for applying Occam's razor and has the additional benefits of simplifying and speeding up model-free analysis. [ABSTRACT FROM AUTHOR]

Two derivatives of Hansenula anomala Flavocytochrome b2 have been prepared, one deprived of the flavin prosthetic group (deflavocytochrome B2), and the other consisting of the heme-h-carrying globule (b2 core). The redox potential of the heme in the two derivatives is -5 (±5) mV and -10 (±5) mV respectively, fairly similar to the value of -20 (±5) mV reported for the holoenzyme, indicating a minor effect of the flavin and of the flavodehydrogenase domain on heme potential. The kinetic of azurin and stellacyanin reduction by both derivatives have been investigated. At pH 7.0, I= 0.2 M and 20°C the second-order rate constants are k = 8 x 105M-1s-1 for azurin reduction by deflavocytochrome b2; k = 1.6 x 106 M-1s-1 for azurin reduction by b2 core; k = 1 x 107 M-1s-1 for stellacyanin reduction by deflavocytochrome b2; k = 3 x 107 M-1s-1 for stellacyanin reduction by b2 core. The change in pH markedly affects the kinetics in the case of azurin, but has no effect on stellacyanin reduction. The change in ionic strength has a significant effect when deflavocytochrome b2 is the reductant, indicating that the flavodehydrogenase domain plays a role in the stabilization of the transient kinetic complex by means of electrostatic interactions. The kinetic results are discussed in the framework of the Marcus theory. [ABSTRACT FROM AUTHOR]

The changes in the degree of phosphorylation of ribosomal protein S6 during the life cycle of the aquatic fungus Blastocladiella emersonii were analyzed by two-dimensional gel electrophoresis. Three phosphorylated derivatives of S6 are present throughout the entire life cycle. However, under certain germination condition, more highly phosphorylated derivatives of S6 appear. Nonetheless, the resumption of protein synthesis that occurs during germination is not dependent on those highly phosphorylated derivatives of S6. The pattern and sites of phosphorylation of S6 labelled in vivo with [32P]orthophosphate have been compared with those of 40S ribosomal subunit labelled in vitro by partially purified protein kinases. Three major phosphopeptides were found in S6 isolated from the zoospore, while six phosphopeptides were found after zoospore germination (in germling cells). The phosphopeptide patterns of S6 phosphorylated by the cAMP-dependent protein kinase and by casein kinases I and II were completely distinct. Only the cAMP-dependent protein kinase gives rise to a phosphopeptide found in 32P-labelled cells, indicating that one of sites phosphorylated in vivo is also phoshorylated in vitro by the cAMP-dependent protein kinase. [ABSTRACT FROM AUTHOR]

A combined reanalysis of the two largest yeast protein-protein interaction studies to date provides a large consolidated data set, with a level of accuracy matching the reliability of small-scale experiments. [ABSTRACT FROM AUTHOR]