Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Sequence Alignment”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8Linked to original sources
PubMed1992

Multiple protein sequence alignment from tertiary structure comparison: assignment of global and residue confidence levels.

An algorithm is presented for the accurate and rapid generation of multiple protein sequence alignments from tertiary structure comparisons. A preliminary multiple sequence alignment is performed using sequence information, which then determines an initial superposition of the structures. A structure comparison algorithm is applied to all pairs of proteins in the superimposed set and a similarity tree calculated. Multiple sequence alignments are then generated by following the tree from the branches to the root. At each branchpoint of the tree, a structure-based sequence alignment and coordinate transformations are output, with the multiple alignment of all structures output at the root. The algorithm encoded in STAMP (STructural Alignment of Multiple Proteins) is shown to give alignments in good agreement with published structural accounts within the dehydrogenase fold domains, globins, and serine proteinases. In order to reduce the need for visual verification, two similarity indices are introduced to determine the quality of each generated structural alignment. Sc quantifies the global structural similarity between pairs or groups of proteins, whereas Pij' provides a normalized measure of the confidence in the alignment of each residue. STAMP alignments have the quality of each alignment characterized by Sc and Pij' values and thus provide a reproducible resource for studies of residue conservation within structural motifs.

Algorithms↗
PubMed2004

Estimates of statistical significance for comparison of individual positions in multiple sequence alignments.

BACKGROUND: Profile-based analysis of multiple sequence alignments (MSA) allows for accurate comparison of protein families. Here, we address the problems of detecting statistically confident dissimilarities between (1) MSA position and a set of predicted residue frequencies, and (2) between two MSA positions. These problems are important for (i) evaluation and optimization of methods predicting residue occurrence at protein positions; (ii) detection of potentially misaligned regions in automatically produced alignments and their further refinement; and (iii) detection of sites that determine functional or structural specificity in two related families. RESULTS: For problems (1) and (2), we propose analytical estimates of P-value and apply them to the detection of significant positional dissimilarities in various experimental situations. (a) We compare structure-based predictions of residue propensities at a protein position to the actual residue frequencies in the MSA of homologs. (b) We evaluate our method by the ability to detect erroneous position matches produced by an automatic sequence aligner. (c) We compare MSA positions that correspond to residues aligned by automatic structure aligners. (d) We compare MSA positions that are aligned by high-quality manual superposition of structures. Detected dissimilarities reveal shortcomings of the automatic methods for residue frequency prediction and alignment construction. For the high-quality structural alignments, the dissimilarities suggest sites of potential functional or structural importance. CONCLUSION: The proposed computational method is of significant potential value for the analysis of protein families.

Amino Acid Sequence↗
PubMed1998

Homology modeling of an RNP domain from a human RNA-binding protein: Homology-constrained energy optimization provides a criterion for distinguishing potential sequence alignments.

We have recently described an automated approach for homology modeling using restrained molecular dynamics and simulated annealing procedures (Li et al, Protein Sci., 6:956-970,1997). We have employed this approach for constructing a homology model of the putative RNA-binding domain of the human RNA-binding protein with multiple splice sites (RBP-MS). The regions of RBP-MS which are homologous to the template protein snRNP U1A were constrained by "homology distance constraints," while the conformation of the non-homologous regions were defined only by a potential energy function. A full energy function without explicit solvent was employed to ensure that the calculated structures have good conformational energies and are physically reasonable. The effects of mis-alignment of the unknown and the template sequences were also explored in order to determine the feasibility of this homology modeling method for distinguishing possible sequence alignments based on considerations of the resulting conformational energies of modeled structures. Differences in the alignments of the unknown and the template sequences result in significant differences in the conformational energies of the calculated homology models. These results suggest that conformational energies and residual constraint violations in these homology-constrained simulated annealing calculations can be used as criteria to distinguish between correct and incorrect sequence alignments and chain folds.

Algorithms↗
PubMedDate not supplied

Faster algorithms for optimal multiple sequence alignment based on pairwise comparisons.

Multiple Sequence Alignment (MSA) is one of the most fundamental problems in computational molecular biology. The running time of the best known scheme for finding an optimal alignment, based on dynamic programming, increases exponentially with the number of input sequences. Hence, many heuristics were suggested for the problem. We consider a version of the MSA problem where the goal is to find an optimal alignment in which matches are restricted to positions in predefined matching segments. We present several techniques for making the dynamic programming algorithm more efficient, while still finding an optimal solution under these restrictions. We prove that it suffices to find an optimal alignment of the predefined sequence segments, rather than single letters, thereby reducing the input size and thus improving the running time. We also identify "shortcuts" that expedite the dynamic programming scheme. Empirical study shows that, taken together, these observations lead to an improved running time over the basic dynamic programming algorithm by 4 to 12 orders of magnitude, while still obtaining an optimal solution. Under the additional assumption that matches between segments are transitive, we further improve the running time for finding the optimal solution by restricting the search space of the dynamic programming algorithm.

Algorithms↗
PubMed2005

Using reconfigurable hardware to accelerate multiple sequence alignment with ClustalW.

Aligning hundreds of sequences using progressive alignment tools such as ClustalW requires several hours on state-of-the-art workstations. We present a new approach to compute multiple sequence alignments in far shorter time using reconfigurable hardware. This results in an implementation of ClustalW with significant runtime savings on a standard off-the-shelf FPGA.

Computers↗
PubMed2004

Identification of regions in multiple sequence alignments thermodynamically suitable for targeting by consensus oligonucleotides: application to HIV genome.

BACKGROUND: Computer programs for the generation of multiple sequence alignments such as "Clustal W" allow detection of regions that are most conserved among many sequence variants. However, even for regions that are equally conserved, their potential utility as hybridization targets varies. Mismatches in sequence variants are more disruptive in some duplexes than in others. Additionally, the propensity for self-interactions amongst oligonucleotides targeting conserved regions differs and the structure of target regions themselves can also influence hybridization efficiency. There is a need to develop software that will employ thermodynamic selection criteria for finding optimal hybridization targets in related sequences. RESULTS: A new scheme and new software for optimal detection of oligonucleotide hybridization targets common to families of aligned sequences is suggested and applied to aligned sequence variants of the complete HIV-1 genome. The scheme employs sequential filtering procedures with experimentally determined thermodynamic cut off points: 1) creation of a consensus sequence of RNA or DNA from aligned sequence variants with specification of the lengths of fragments to be used as oligonucleotide targets in the analyses; 2) selection of DNA oligonucleotides that have pairing potential, greater than a defined threshold, with all variants of aligned RNA sequences; 3) elimination of DNA oligonucleotides that have self-pairing potentials for intra- and inter-molecular interactions greater than defined thresholds. This scheme has been applied to the HIV-1 genome with experimentally determined thermodynamic cut off points. Theoretically optimal RNA target regions for consensus oligonucleotides were found. They can be further used for improvement of oligo-probe based HIV detection techniques. CONCLUSIONS: A selection scheme with thermodynamic thresholds and software is presented in this study. The package can be used for any purpose where there is a need to design optimal consensus oligonucleotides capable of interacting efficiently with hybridization targets common to families of aligned RNA or DNA sequences. Our thermodynamic approach can be helpful in designing consensus oligonucleotides with consistently high affinity to target variants in evolutionary related genes or genomes.

Base Sequence↗
PubMed2005

The ubiquitin domain superfold: structure-based sequence alignments and characterization of binding epitopes.

Ubiquitin-like domains are present, apart from ubiquitin-like proteins themselves, in many multidomain proteins involved in different signal transduction processes. The sequence conservation for all ubiquitin superfold family members is rather poor, even between subfamily members, leading to mistakes in sequence alignments using conventional sequence alignment methods. However, a correct alignment is essential, especially for in silico methods that predict binding partners on the basis of sequence and structure. In this study, using 3D-structural information we have generated and manually corrected sequence alignments for proteins of the five ubiquitin superfold subfamilies. On the basis of this alignment, we suggest domains for which structural information will be useful to allow homology modelling. In addition, we have analysed the energetic and electrostatic properties of ubiquitin-like domains in complex with various functional binding proteins using the protein design algorithm FoldX. On the basis of an in silico alanine-scanning mutagenesis, we provide a detailed binding epitope mapping of the hotspots of the ubiquitin domain fold, involved in the interaction with different domains and proteins. Finally, we provide a consensus fingerprint sequence that identifies all sequences described to belong to the ubiquitin superfold family. It is possible that the method that we describe may be applied to other domain families sharing a similar fold but having low levels of sequence homology.

Amino Acid Sequence↗
PubMed2004

Statistical methods for identifying conserved residues in multiple sequence alignment.

The assessment of residue conservation in a multiple sequence alignment is a central issue in bioinformatics. Conserved residues and regions are used to determine structural and functional motifs or evolutionary relationships between the sequences of a multiple sequence alignment. For this reason, residue conservation is a valuable measure for database and motif search or for estimating the quality of alignments. In this paper, we present statistical methods for identifying conserved residues in multiple sequence alignments. While most earlier studies examine the positional conservation of the alignment, we focus on the detection of individual conserved residues at a position. The major advantages of multiple comparison methods originate from their ability to select conserved residues simultaneously and to consider the variability of the residue estimates. Large-scale simulations were used for the comparative analysis of the methods. Practical performance was studied by comparing the structurally and functionally important residues of Src homology 2 (SH2) domains to the assignments of the conservation indices. The applicability of the indices was also compared in three additional protein families comprising different degrees of entropy and variability in alignment positions. The results indicate that statistical multiple comparison methods are sensitive and reliable in identifying conserved residues.

Journal Article↗
PubMed1999

An iterative structure-assisted approach to sequence alignment and comparative modeling.

Correct alignment of the sequence of a target protein with those of homologues of known three-dimensional structure is a key step in comparative modeling. Usually an iterative approach that takes account of the local and overall structural features is required. We describe such an approach that exploits databases of structural alignments of homologous proteins (HOMSTRAD, http:/(/)www-cryst.bioc.cam.ac.uk/ approximately homstrad) and protein superfamilies (CAMPASS, http:/(/)www-cryst.bioc.cam.ac.uk/ approximately campass), in which structure-based alignments are analyzed and formatted with the program JOY (http:/(/)www-cryst.bioc.cam.ac.uk/ approximately joy) to reveal conserved local structural features. The databases facilitate the recognition of a family or superfamily, they assist in the selection of useful parent structures, they are helpful in alignment of the target sequences with the parent set, and are useful for deriving relationships that can be used in validating models. In the iterative approach, a model is constructed on the basis of the proposed sequence alignment and this is then reexpressed in the JOY format and realigned with the parent set. This is repeated until the model and sequence alignment is optimized. We examine the case for comparison and use of multiple structures of family members, rather than a single parent structure. We use the targets attempted by our group in CASP3 to assess the value of such procedures.

Algorithms↗
PubMed2006

Fuzzy Hidden Markov Models: a new approach in multiple sequence alignment.

This paper proposes a novel method for aligning multiple genomic or proteomic sequences using a fuzzyfied Hidden Markov Model (HMM). HMMs are known to provide compelling performance among multiple sequence alignment (MSA) algorithms, yet their stochastic nature does not help them cope with the existing dependence among the sequence elements. Fuzzy HMMs are a novel type of HMMs based on fuzzy sets and fuzzy integrals which generalizes the classical stochastic HMM, by relaxing its independence assumptions. In this paper, the fuzzy HMM model for MSA is mathematically defined. New fuzzy algorithms are described for building and training fuzzy HMMs, as well as for their use in aligning multiple sequences. Fuzzy HMMs can also increase the model capability of aligning multiple sequences mainly in terms of computation time. Modeling the multiple sequence alignment procedure with fuzzy HMMs can yield a robust and time-effective solution that can be widely used in bioinformatics in various applications, such as protein classification, phylogenetic analysis and gene prediction, among others.

Base Sequence↗
PubMed2002

DNA multiple sequence alignments.

In this chapter we examine the procedure of multiple sequence alignment. We first examine the heuristic procedures commonly used in multiple sequence alignment. Next we examine sources of ambiguity involved in the alignment procedure. We suggest that several alignment parameters be employed to examine alignment sensitivity. We end by presenting an experiment with humans showing the ambiguity involved in manual alignment.

Humans↗
PubMed2001

Pairwise sequence alignment below the twilight zone.

Improved sequence alignment at low pairwise identity is important for identifying potential remote homologues in database searches and for obtaining accurate alignments as a prelude to modeling structures by homology. Our work is motivated by two observations: structural data provide superior training examples for developing techniques to improve the alignment of remote homologues; and general substitution patterns for remote homologues differ from those of closely related proteins. We introduce a new set of amino acid residue interchange matrices built from structural superposition data. These matrices exploit known structural homology as a means of characterizing the effect evolution has on residue-substitution profiles. Given their origin, it is not surprising that the individual residue-residue interchange frequencies are chemically sensible. The structural interchange matrices show a significant increase both in pairwise alignment accuracy and in functional annotation/fold recognition accuracy across distantly related sequences. We demonstrate improved pairwise alignment by using superpositions of homologous domains extracted from a structural database as a gold standard and go on to show an increase in fold recognition accuracy using a database of homologous fold families. This was applied to the unassigned open reading frames from the genome of Helicobacter pylori to identify five matches, two of which are not represented by new annotations in the sequence databases. In addition, we describe a new cyclic permutation strategy to identify distant homologues that experienced gene duplication and subsequent deletions. Using this method, we have identified a potential homologue to one additional previously unassigned open reading frame from the H. pylori genome.

Amino Acid Sequence↗
PubMed2006

Two Sample Logo: a graphical representation of the differences between two sets of sequence alignments.

SUMMARY: Two Sample Logo is a web-based tool that detects and displays statistically significant differences in position-specific symbol compositions between two sets of multiple sequence alignments. In a typical scenario, two groups of aligned sequences will share a common motif but will differ in their functional annotation. The inclusion of the background alignment provides an appropriate underlying amino acid or nucleotide distribution and addresses intersite symbol correlations. In addition, the difference detection process is sensitive to the sizes of the aligned groups. Two Sample Logo extends WebLogo, a widely-used sequence logo generator. The source code is distributed under the MIT Open Source license agreement and is available for download free of charge.

Algorithms↗
PubMed2000

Multiple sequence alignment in phylogenetic analysis.

Multiple sequence alignment is discussed in light of homology assessments in phylogenetic research. Pairwise and multiple alignment methods are reviewed as exact and heuristic procedures. Since the object of alignment is to create the most efficient statement of initial homology, methods that minimize nonhomology are to be favored. Therefore, among all possible alignments, the one that satisfies the phylogenetic optimality criterion the best should be considered the best alignment. Since all homology statements are subject to testing and explanation this way, consistency of optimality criteria is desirable. This consistency is based on the treatment of alignment gaps as character information and the consistent use of a cost function (e.g., insertion-deletion, transversion, and transition) through analysis from alignment to phylogeny reconstruction. Cost functions are not subject to testing via inspection; hence the assumptions they make should be examined by varying the assumed values in a sensitivity analysis context to test for the robustness of results. Agreement among data may be used to choose an optimal solution set from all of those examined through parameter variation. This idea of consistency between assumption and analysis through alignment and cladogram reconstruction is not limited to parsimony analysis and could and should be applied to other forms of analysis such as maximum likelihood.

Algorithms↗
PubMed2004

MSAT: a multiple sequence alignment tool based on TOPS.

This article describes the development of a new method for multiple sequence alignment based on fold-level protein structure alignments, which provides an improvement in accuracy compared with the most commonly used sequence-only-based techniques. This method integrates the widely used, progressive multiple sequence alignment approach ClustalW with the Topology of Protein Structure (TOPS) topology-based alignment algorithm. The TOPS approach produces a structural alignment for the input protein set by using a topology-based pattern discovery program, providing a set of matched sequence regions that can be used to guide a sequence alignment using ClustalW. The resulting alignments are more reliable than a sequence-only alignment, as determined by 20-fold cross-validation with a set of 106 protein examples from the CATH database, distributed in seven superfold families. The method is particularly effective for sets of proteins that have similar structures at the fold level but low sequence identity. The aim of this research is to contribute towards bridging the gap between protein sequence and structure analysis, in the hope that this can be used to assist the understanding of the relationship between sequence, structure and function. The tool is available at http://balabio.dcs.gla.ac.uk/msat/.

Algorithms↗
PubMed1998

Nucleotide and amino acid sequence alignment for human killer cell inhibitory receptors (KIR), 1998.

We present alignments of nucleotide sequences and deduced amino acid sequences for all currently identified killer cell inhibitory receptors (KIR). The genes for these receptors have been localized to human chromosome 19q13.4 and constitute a large gene family. They all encode structures typical of type I transmembrane molecules belonging to the immunoglobulin superfamily (Ig-SF). Extensive polymorphism exists within the genes and many of the currently identified cDNA clones represent alternatively spliced forms of previously reported full-length clones. The sequence alignments have been posted on the World Wide Web and are accessible at the Tissue Antigens web site at: http://www.tissue-antigens.dk/kir-align.html. The alignments will be updated at intervals.

Amino Acid Sequence↗
PubMed1996

The HSSP database of protein structure-sequence alignments.

HSSP is a derived database merging structural three dimensional (3-D) and sequence one dimensional(1-D) information. For each protein of known 3-D structure from the Protein Data Bank (PDB), the database has a multiple sequence alignment of all available homologues and a sequence profile characteristic of the family. The list of homologues is the result of a database search in Swissprot using a position-weighted dynamic programming method for sequence profile alignment (MaxHom). The database is updated frequently. The listed homologues are very likely to have the same 3-D structure as the PDB protein to which they have been aligned. As a result, the database is not only a database of aligned sequence families, but also a database of implied secondary and tertiary structures covering 27% of all Swissprot-stored sequences.

Amino Acid Sequence↗
PubMed2006

The iRMSD: a local measure of sequence alignment accuracy using structural information.

MOTIVATION: We introduce the iRMSD, a new type of RMSD, independent from any structure superposition and suitable for evaluating sequence alignments of proteins with known structures. RESULTS: We demonstrate that the iRMSD is equivalent to the standard RMSD although much simpler to compute and we also show that it is suitable for comparing sequence alignments and benchmarking multiple sequence alignment methods. We tested the iRMSD score on 6 established multiple sequence alignment packages and found the results to be consistent with those obtained using an established reference alignment collection like Prefab. AVAILABILITY: The iRMSD is part of the T-Coffee package and is distributed as an open source freeware (http://www.tcoffee.org/).

Algorithms↗