A rapid protein structure alignment algorithm based on a text modeling technique

Structural alignment of proteins is widely used in various fields of structural biology. In order to further improve the quality of alignment, we describe an algorithm for structural alignment based on text modelling techniques. The technique firstly superimposes secondary structure elements of two proteins and then, models the 3D-structure of the protein in a sequence of alphabets. These sequences are utilized by a step-by-step sequence alignment procedure to align two protein structures. A benchmark test was organized on a set of 200 non-homologous proteins to evaluate the program and compare it to state of the art programs, e.g. CE, SAL, TM-align and 3D-BLAST. On average, the results of all-against-all structure comparison by the program have a competitive accuracy with CE and TM-align where the algorithm has a high running speed like 3D-BLAST.     

A rapid method for exploring the protein structure universe

We have developed an automatic protein fingerprinting method for the evaluation of protein structural similarities based on secondary structure element compositions, spatial arrangements, lengths, and topologies. This method can rapidly identify proteins sharing structural homologies as we demonstrate with five test cases: the globins, the mammalian trypsinlike serine proteases, the immunoglobulins, the cupredoxins, and the actinlike ATPase domain-containing proteins. Principal components analysis of the similarity distance matrix calculated from an all-by-all comparison of 1,031 unique chains in the Protein Data Bank has produced a distribution of structures within a high-dimensional structural space. Fifty percent of the variance observed for this distribution is bounded by six axes, two of which encode structural variability within two large families, the immunoglobulins and the trypsinlike serine proteases. Many aspects of the spatial distribution remain stable upon reduction of the database to 140 proteins with minimal family overlap. The axes correlated with specific structural families are no longer observed. A clear hierarchy of organization is seen in the arrangement of protein structures in the universe. At the highest level, protein structures populate regions corresponding to the all-alpha, all-beta, and alpha/beta superfamilies. Large protein families are arranged along family-specific axes, forming local densely populated regions within the space. The lowest level of organization is intrafamilial; homologous structures are ordered by variations in peripheral secondary structure elements or by conformational shifts in the tertiary structure.     

A holistic approach to protein structure alignment

A method of protein structure comparison developed previously is extended to incorporate other aspects of protein structure in addition to the inter-atomic vectors on which it was originally based. Each additional aspect, which induced hydrogen bonding, solvent exposure, torsional angles and sequence, was introduced separately and evaluated for its ability to improve alignment quality. The components were then combined, suitably weighted, to produce a more holistic comparison method. The method was tested on a group of remotely related beta/alpha type proteins that share a common feature in their overall chain fold. The results indicated that while the original inter-atomic vector component was sufficient to give the correct alignment of most pairs of topologically equivalent proteins, the inclusion of hydrogen bonds, torsion angles and a measure of solvent exposure led to improvements in the more difficult comparisons. Consideration of amino acid properties, including hydrophobicity, had no beneficial effect. The failure of the latter component was not unexpected considering the almost total lack of sequence similarity among the proteins considered.     

A spectral approach to protein structure alignment

A new intrinsic geometry based on a spectral analysis is used to motivate methods for aligning protein folds. The geometry is induced by the fact that a distance matrix can be scaled so that its eigenvalues are positive. We provide a mathematically rigorous development of the intrinsic geometry underlying our spectral approach and use it to motivate two alignment algorithms. The first uses eigenvalues alone and dynamic programming to quickly compute a fold alignment. Family identification results are reported for the Skolnick40 and Proteus300 data sets. The second algorithm extends our spectral method by iterating between our intrinsic geometry and the 3D geometry of a fold to make high-quality alignments. Results and comparisons are reported for several difficult fold alignments. The second algorithm's ability to correctly identify fold families in the Skolnick40 and Proteus300 data sets is also established.     

A parameterized algorithm for protein structure alignment.

This paper proposes a parameterized polynomial time approximation scheme (PTAS) for aligning two protein structures, in the case where one protein structure is represented by a contact map graph and the other by a contact map graph or a distance matrix. If the sequential order of alignment is not required, the time complexity is polynomial in the protein size and exponential with respect to two parameters D(u)/D(l) and D(c)/D(l), which usually can be treated as constants. In particular, D(u) is the distance threshold determining if two residues are in contact or not, D(c) is the maximally allowed distance between two matched residues after two proteins are superimposed, and D(l) is the minimum inter-residue distance in a typical protein. This result clearly demonstrates that the computational hardness of the contact map based protein structure alignment problem is related not to protein size but to several parameters modeling the problem. The result is achieved by decomposing the protein structure using tree decomposition and discretizing the rigid-body transformation space. Preliminary experimental results indicate that on a Linux PC, it takes from ten minutes to one hour to align two proteins with approximately 100 residues.     

A novel Markov pairwise protein sequence alignment method for sequence comparison

The Smith-Waterman (SW) algorithm is a typical technique for local sequence alignment in computational biology. However, the SW algorithm does not consider the local behaviours of the amino acids, which may result in loss of some useful information. Inspired by the success of Markov Edit Distance (MED) method, this paper therefore proposes a novel Markov pairwise protein sequence alignment (MPPSA) method that takes the local context dependencies into consideration. The numerical results have shown its superiority to the SW for pairwise protein sequence comparison.     

Fast structure alignment for protein databank searching.

A fast method is described for searching and analyzing the protein structure databank. It uses secondary structure followed by residue matching to compare protein structures and is developed from a previous structural alignment method based on dynamic programming. Linear representations of secondary structures are derived and their features compared to identify equivalent elements in two proteins. The secondary structure alignment then constrains the residue alignment, which compares only residues within aligned secondary structures and with similar buried areas and torsional angles. The initial secondary structure alignment improves accuracy and provides a means of filtering out unrelated proteins before the slower residue alignment stage. It is possible to search or sort the protein structure databank very quickly using just secondary structure comparisons. A search through 720 structures with a probe protein of 10 secondary structures required 1.7 CPU hours on a Sun 4/280. Alternatively, combined secondary structure and residue alignments, with a cutoff on the secondary structure score to remove pairs of unrelated proteins from further analysis, took 10.1 CPU hours. The method was applied in searches on different classes of proteins and to cluster a subset of the databank into structurally related groups. Relationships were consistent with known families of protein structure.     

A rapid method for protein extraction from fission yeast

Researchers working with fission yeast conduct protein extraction widely and frequently, but this includes the handling of glass beads, and hence is laborious and cumbersome, especially when dealing with a large number of samples. Here we describe a rapid and reliable method for preparing protein extract from fission yeast, one which is applicable to routine western blotting.     

A rapid method for determining protein kinase phosphorylation specificity

Selection of target substrates by protein kinases is strongly influenced by the amino acid sequence surrounding the phosphoacceptor site. Identification of the preferred peptide phosphorylation motif for a given kinase permits the production of efficient peptide substrates and greatly simplifies the mapping of phosphorylation sites in protein substrates. Here we describe a combinatorial peptide library method that allows rapid generation of phosphorylation motifs for serine/threonine kinases.     

A rapid method for removal of detergents from protein solution

A simple and rapid technique is described for the removal of Triton X-100, deoxycholate, and cholate from protein solutions. The method involves a 2-min centrifugation of the sample on a Bio-Beads SM-2 bed prepared in a microcentrifuge tube and is suitable for multiple assays of 0.05- to 0.45-ml samples. Another advantage of this method is the high recovery of proteins without dilution of the sample.     

ProSup: a refined tool for protein structure alignment

We investigated and optimized a method for structure comparison which is based on rigid body superimposition. The method maximizes the number of structurally equivalent residues while keeping the root mean square deviation constant. The resulting number of equivalent residues then provides an adequate similarity measure, which is easy to interpret. We demonstrate that the approach is able to detect remote structural similarity. We show that the number of equivalent residues is a suitable measure for ranking database searches and that the results are in good agreement with expert knowledge protein structure classification. Structure comparison frequently has multiple solutions. The approach that we use provides a range of alternative alignments rather a single solution. We discuss the nature of alternative solutions on several examples.     

Matt: local flexibility aids protein multiple structure alignment

Even when there is agreement on what measure a protein multiple structure alignment should be optimizing, finding the optimal alignment is computationally prohibitive. One approach used by many previous methods is aligned fragment pair chaining, where short structural fragments from all the proteins are aligned against each other optimally, and the final alignment chains these together in geometrically consistent ways. Ye and Godzik have recently suggested that adding geometric flexibility may help better model protein structures in a variety of contexts. We introduce the program Matt (Multiple Alignment with Translations and Twists), an aligned fragment pair chaining algorithm that, in intermediate steps, allows local flexibility between fragments: small translations and rotations are temporarily allowed to bring sets of aligned fragments closer, even if they are physically impossible under rigid body transformations. After a dynamic programming assembly guided by these “bent” alignments, geometric consistency is restored in the final step before the alignment is output. Matt is tested against other recent multiple protein structure alignment programs on the popular Homstrad and SABmark benchmark datasets. Matt's global performance is competitive with the other programs on Homstrad, but outperforms the other programs on SABmark, a benchmark of multiple structure alignments of proteins with more distant homology. On both datasets, Matt demonstrates an ability to better align the ends of α-helices and β-strands, an important characteristic of any structure alignment program intended to help construct a structural template library for threading approaches to the inverse protein-folding problem. The related question of whether Matt alignments can be used to distinguish distantly homologous structure pairs from pairs of proteins that are not homologous is also considered. For this purpose, a p-value score based on the length of the common core and average root mean squared deviation (RMSD) of Matt alignments is shown to largely separate decoys from homologous protein structures in the SABmark benchmark dataset. We postulate that Matt's strong performance comes from its ability to model proteins in different conformational states and, perhaps even more important, its ability to model backbone distortions in more distantly related proteins.     

A rapid method to improve protein detection by indirect ELISA

The enzyme-linked immunosorbant assay (ELISA) is a rapid, high-throughput, quantitative immunoassay for the selective detection of target antigens. The general principle behind an ELISA is antibody mediated capture and detection of an antigen with a measurable substrate. Numerous incarnations of the ELISA have resulted in its commercialization for sensitive diagnostic applications using a variety of detection platforms. Many of these applications require a pair of antibodies necessary for the capture and detection of a specific antigen (cELISA) in defined substrates. However, the availability of cELISA for target antigens is limited and thus restricts the use of this technique for quantitative measure of antigens during discovery. Alternatively, the indirect ELISA (iELISA) requires only a single antibody directed against a target antigen that has been immobilized to a surface. Unlike the cELISA, which uses an immobilized capture antibody that can bind a native antigen in solution followed by a detector antibody that binds captured antigen, the iELISA uses an antibody the binds directly to an immobilized antigen for detection. Although the iELISA may lack the sensitivity of a cELISA, its requirement of only a single antigen specific antibody makes it a simple technique for evaluating the relative difference in the level of target protein expression between samples. However, many antibodies that work effectively to detect protein antigens in other immunoassays such as Western blotting or immunohistochemistry fail to work in microplate based iELISA. Although these alternate immunoassay methods are useful for qualitative determination of target antigens, they provide limited quantitative information, limiting the assessment of sample specific differences in protein expression. We hypothesized that protein conformation following adsorption on the plastic surface of microplates impedes antibody epitope binding and this restriction could be overcome by a short chemical denaturation step. In this report we define a rapid method to assess the utility of an antibody for iELISA application and demonstrate a significant improvement in both qualitative and quantitative protein detection after chemical denaturation using defined assay conditions.     

A simple and rapid method for isolating myelin basic protein

The conduction of impulses along axons of nerves is facilitated by the myelin sheath, composed of proteins and lipid. Myelin basic proteins (MBPs) are extrinsic membrane proteins that play an important role in the structural organization of the myelin sheath. In the central nervous system, MBPs account for 30-40% of total protein. The traditional method of MBP isolation involves the use of chloroform-ethanol, which would destroy the native form of MBP. A modified method for maintaining its native form was developed. The white matter of porcine brain was directly extracted by buffers containing different concentrations of sodium chloride owing to MBP solubilized at high concentration of NaCl. The MBP was further purified by cation exchange chromatography and buffers containing glycine and salts. Purified MBP were consistently obtained by this method.     

SAS-Pro: simultaneous residue assignment and structure superposition for protein structure alignment

Protein structure alignment is the problem of determining an assignment between the amino-acid residues of two given proteins in a way that maximizes a measure of similarity between the two superimposed protein structures. By identifying geometric similarities, structure alignment algorithms provide critical insights into protein functional similarities. Existing structure alignment tools adopt a two-stage approach to structure alignment by decoupling and iterating between the assignment evaluation and structure superposition problems. We introduce a novel approach, SAS-Pro, which addresses the assignment evaluation and structure superposition simultaneously by formulating the alignment problem as a single bilevel optimization problem. The new formulation does not require the sequentiality constraints, thus generalizing the scope of the alignment methodology to include non-sequential protein alignments. We employ derivative-free optimization methodologies for searching for the global optimum of the highly nonlinear and non-differentiable RMSD function encountered in the proposed model. Alignments obtained with SAS-Pro have better RMSD values and larger lengths than those obtained from other alignment tools. For non-sequential alignment problems, SAS-Pro leads to alignments with high degree of similarity with known reference alignments. The source code of SAS-Pro is available for download at http://eudoxus.cheme.cmu.edu/saspro/SAS-Pro.html.     

A method for the rapid,automated filtration of protein hydrolyzates

A method for the automated filtration of protein hydrolyzates prior to amino acid analysis is described. Minor modification of a Technicon Sampler II enables it to function simultaneously as a sampler and a filtrate collector. Samples are drawn from cups in the sampler tray and are forced through a Teflon filter (pore size, 0.2 μm) in a Millipore Swinnex filter holder by a variable-speed Technicon proportioning pump. The filtrates are collected in cups in the sampler tray opposite those containing unfiltered hydrolyzates. Using this technique, 12 hydrolyzates can be filtered in 25 min compared to the approximately 2 h of technician time required for their manual filtration. Aliquots from each of 48 samples representing different proteins and hydrolysis conditions are filtered manually and by the automated technique. Analysis of variance of the resulting recoveries of each amino acid indicate little likelihood of effects due to filtration method.     

A rapid method for assessing the RNA-binding potential of a protein

In recent years, evidence has emerged for the existence of many diverse types of RNA, which play roles in a wide range of biological processes in all kingdoms of life. These molecules generally do not, however, act in isolation, and identifying which proteins partner with RNA is a major challenge. Many methods, in vivo and in vitro, have been used to address this question, including combinatorial or high-throughput approaches, such as systematic evolution of ligands, cross-linking and immunoprecipitation and RNA immunoprecipitation combined with deep sequencing. However, most of these methods are not trivial to pursue and often require substantial optimization before results can be achieved. Here, we demonstrate a simple technique that allows one to screen proteins for RNA-binding properties in a gel-shift experiment and can be easily implemented in any laboratory. This assay should be a useful first-pass tool for assessing whether a protein has RNA- or DNA-binding properties, prior to committing resources to more complex procedures.     

A method for rapid regulation of protein expression in Trypanosoma cruzi

Analysis of gene function in Trypanosoma cruzi is limited due to the absence of rapid, simple and reversible genetic tools to regulate gene and corresponding protein expression. We have designed a modified pTREX vector which uses an N-terminal fusion of a ligand-controlled destabilisation domain (ddFKBP) to a gene/protein of interest. This vector allows rapid and reversible protein expression and efficient functional analysis of proteins in different T. cruzi life cycle stages.     

A pentapeptide-based method for protein secondary structure prediction

We present a new method for protein secondary structure prediction, based on the recognition of well-defined pentapeptides, in a large databank. Using a databank of 635 protein chains, we obtained a success rate of 68.6%. We show that progress is achieved when the databank is enlarged, when the 20 amino acids are adequately grouped in 10 sets and when more pentapeptides are attributed one of the defined conformations, alpha-helices or beta-strands. The analysis of the model indicates that the essential variable is the number of pentapeptides of well-defined structure in the database. Our model is simple, does not rely on arbitrary parameters and allows the analysis in detail of the results of each chosen hypothesis.