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PubMed1997

The HSSP database of protein structure-sequence alignments.

HSSP is a derived database merging structural (3-D) and sequence (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 29% of all SwissProt-stored sequences.

Amino Acid Sequence↗

PubMed1999

A probabilistic treatment of phylogeny and sequence alignment.

Carrying out simultaneous tree-building and alignment of sequence data is a difficult computational task, and the methods currently available are either limited to a few sequences or restricted to highly simplified models of alignment and phylogeny. A method is given here for overcoming these limitations by Bayesian sampling of trees and alignments simultaneously. The method uses a standard substitution matrix model for residues together with a hidden Markov model structure that allows affine gap penalties. It escapes the heavy computational burdens of other models by using an approximation called the "*" rule, which replaces missing data by a sum over all possible values of variables. The behavior of the model is demonstrated on test sets of globins.

Bayes Theorem↗

PubMed1993

Constrained sequence alignment.

This paper presents a dynamic programming algorithm for aligning two sequences when the alignment is constrained to lie between two arbitrary boundary lines in the dynamic programming matrix. For affine gap penalties, the algorithm requires only O(F) computations time and O(M+N) space, when F is the area of the feasible region and M and N are the sequence lengths. The result extends to concave gap penalities, with somewhat increased time and space bounds.

Algorithms↗

PubMed1994

The prediction and orientation of alpha-helices from sequence alignments: the combined use of environment-dependent substitution tables, Fourier transform methods and helix capping rules.

Amino acid substitution tables are used to estimate the extent to which amino acids in families of homologous proteins are exposed to the solvent. The approach depends on the comparison of difference environment-dependent tables for solvent accessible/inaccessible residues with amino acid substitutions at each position in an aligned set of sequences. The periodicity in the predicted accessible/inaccessible residues is calculated using a Fourier transform procedure modified from that used to calculate hydrophobic moments. alpha-Helices are identified from the characteristic periodicities and the solvent accessible face of the helix is defined. The initial helix predictions are refined using rules for identifying the N- and C-termini of helices from sequence alignments. These rules have been defined from a study of protein structures. The combined method correctly predicts 79% of the residues in helices and incorrectly predicts only 12% of the nonhelical residues as helical. In addition, since the method is reliable at predicting the correct number of helices in the correct position in the sequence and since it also predicts the internal face of each helix, the results can be used to postulate 3-D arrangements of the secondary structure elements.

Amino Acid Sequence↗

PubMed2003

APDB: a novel measure for benchmarking sequence alignment methods without reference alignments.

MOTIVATION: We describe APDB, a novel measure for evaluating the quality of a protein sequence alignment, given two or more PDB structures. This evaluation does not require a reference alignment or a structure superposition. APDB is designed to efficiently and objectively benchmark multiple sequence alignment methods. RESULTS: Using existing collections of reference multiple sequence alignments and existing alignment methods, we show that APDB gives results that are consistent with those obtained using conventional evaluations. We also show that APDB is suitable for evaluating sequence alignments that are structurally equivalent. We conclude that APDB provides an alternative to more conventional methods used for benchmarking sequence alignment packages.

Algorithms↗

PubMed2006

Refining multiple sequence alignments with conserved core regions.

Accurate multiple sequence alignments of proteins are very important to several areas of computational biology and provide an understanding of phylogenetic history of domain families, their identification and classification. This article presents a new algorithm, REFINER, that refines a multiple sequence alignment by iterative realignment of its individual sequences with the predetermined conserved core (block) model of a protein family. Realignment of each sequence can correct misalignments between a given sequence and the rest of the profile and at the same time preserves the family's overall block model. Large-scale benchmarking studies showed a noticeable improvement of alignment after refinement. This can be inferred from the increased alignment score and enhanced sensitivity for database searching using the sequence profiles derived from refined alignments compared with the original alignments. A standalone version of the program is available by ftp distribution (ftp://ftp.ncbi.nih.gov/pub/REFINER) and will be incorporated into the next release of the Cn3D structure/alignment viewer.

Algorithms↗

PubMed2005

Recurrent structural RNA motifs, Isostericity Matrices and sequence alignments.

The occurrences of two recurrent motifs in ribosomal RNA sequences, the Kink-turn and the C-loop, are examined in crystal structures and systematically compared with sequence alignments of rRNAs from the three kingdoms of life in order to identify the range of the structural and sequence variations. Isostericity Matrices are used to analyze structurally the sequence variations of the characteristic non-Watson-Crick base pairs for each motif. We show that Isostericity Matrices for non-Watson-Crick base pairs provide important tools for deriving the sequence signatures of recurrent motifs, for scoring and refining sequence alignments, and for determining whether motifs are conserved throughout evolution. The systematic use of Isostericity Matrices identifies the positions of the insertion or deletion of one or more nucleotides relative to the structurally characterized examples of motifs and, most importantly, specifies whether these changes result in new motifs. Thus, comparative analysis coupled with Isostericity Matrices allows one to produce and refine structural sequence alignments. The analysis, based on both sequence and structure, permits therefore the evaluation of the conservation of motifs across phylogeny and the derivation of rules of equivalence between structural motifs. The conservations observed in Isostericity Matrices form a predictive basis for identifying motifs in sequences.

Base Pairing↗

PubMed2005

Manipulating multiple sequence alignments via MaM and WebMaM.

MaM is a software tool that processes and manipulates multiple alignments of genomic sequence. MaM computes the exact location of common repeat elements, exons and unique regions within aligned genomics sequences using a variety of user identified programs, databases and/or tables. The program can extract subalignments, corresponding to these various regions of DNA to be analyzed independently or in conjunction with other elements of genomic DNA. Graphical displays further allow an assessment of sequence variation throughout these different regions of the aligned sequence, providing separate displays for their repeat, non-repeat and coding portions of genomic DNA. The program should facilitate the phylogenetic analysis and processing of different portions of genomic sequence as part of large-scale sequencing efforts. MaM source code is freely available for non-commercial use at http://compbio.cs.sfu.ca/MAM.htm; and the web interface WebMaM is hosted at http://atgc.lirmm.fr/mam.

Exons↗

PubMed2003

POAVIZ: a Partial order multiple sequence alignment visualizer.

SUMMARY: POAVIZ creates a visualization of a multiple sequence alignment that makes clear the overall structure of how sequences match and diverge in the alignment. POAVIZ can construct visualizations from any multiple sequence alignment source (e.g. PIR and CLUSTAL formats), and is valuable for revealing complex branching structure (such as domains, large-scale insertions / deletions or recombinations), especially in partnership with the Partial Order Alignment (POA) multiple sequence alignment program. AVAILABILITY: The Partial Order multiple sequence Alignment Visualizer (POAVIZ) program is available at http://www.bioinformatics.ucla.edu/poa

Algorithms↗

PubMed1996

Analysis of human interferon-alpha gene promoters by multiple sequence alignment.

A map of conserved motifs within 11 human interferon-alpha gene promoters was developed using multiple sequence alignment. Multiple sequence alignment revealed the highly conserved structure of the virus-response element and a second region immediately upstream of the tata box. Homolog analysis indicated six families of potential promoter elements: (1) tata boxes, (2) GTATGT motifs, (3) virus-response elements, (4) distal putative interferon regulatory factor binding sites, (5) proximal putative interferon regulatory factor binding sites, and (6) TG sequences. On the basis of conserved promoter elements, a theoretical model of human interferon-alpha gene promoter organization was advanced. Transcriptional regulation of human interferon-alpha gene expression is controlled by a tata box and four regulatory domains. Experimental verification is necessary to confirm the predicted transcriptional control sequences. Proposed experimentation will generate insight into the differential transcriptional regulation of human interferon-alpha gene expression.

Amino Acid Sequence↗

PubMed2003

SATCHMO: sequence alignment and tree construction using hidden Markov models.

MOTIVATION: Aligning multiple proteins based on sequence information alone is challenging if sequence identity is low or there is a significant degree of structural divergence. We present a novel algorithm (SATCHMO) that is designed to address this challenge. SATCHMO simultaneously constructs a tree and a set of multiple sequence alignments, one for each internal node of the tree. The alignment at a given node contains all sequences within its sub-tree, and predicts which positions in those sequences are alignable and which are not. Aligned regions therefore typically get shorter on a path from a leaf to the root as sequences diverge in structure. Current methods either regard all positions as alignable (e.g. ClustalW), or align only those positions believed to be homologous across all sequences (e.g. profile HMM methods); by contrast SATCHMO makes different predictions of alignable regions in different subgroups. SATCHMO generates profile hidden Markov models at each node; these are used to determine branching order, to align sequences and to predict structurally alignable regions. RESULTS: In experiments on the BAliBASE benchmark alignment database, SATCHMO is shown to perform comparably to ClustalW and the UCSC SAM HMM software. Results using SATCHMO to identify protein domains are demonstrated on potassium channels, with implications for the mechanism by which tumor necrosis factor alpha affects potassium current. AVAILABILITY: The software is available for download from http://www.drive5.com/lobster/index.htm

Algorithms↗

PubMed2004

Contact-based sequence alignment.

This paper introduces the novel method of contact-based protein sequence alignment, where structural information in the form of contact mutation probabilities is incorporated into an alignment routine using contact-mutation matrices (CAO: Contact Accepted mutatiOn). The contact-based alignment routine optimizes the score of matched contacts, which involves four (two per contact) instead of two residues per match in pairwise alignments. The first contact refers to a real side-chain contact in a template sequence with known structure, and the second contact is the equivalent putative contact of a homologous query sequence with unknown structure. An algorithm has been devised to perform a pairwise sequence alignment based on contact information. The contact scores were combined with PAM-type (Point Accepted Mutation) substitution scores after parameterization of gap penalties and score weights by means of a genetic algorithm. We show that owing to the structural information contained in the CAO matrices, significantly improved alignments of distantly related sequences can be obtained. This has allowed us to annotate eight putative Drosophila IGF sequences. Contact-based sequence alignment should therefore prove useful in comparative modelling and fold recognition.

Algorithms↗

PubMed2000

Multiple protein sequence alignment using double-dynamic programming.

A method of multiple sequence alignment is described based on the double dynamic programming (DDP) algorithm previously used for treating structural constraints encountered in structure comparison and threading. Following these applications, the inconsistencies that emerge when trying to combine pair-wise alignments into a multiple alignment are reconciled by summing all the, possibly inconsistent, paths (low-level alignments) into a matrix which is then used to provide a final (high-level) alignment. This process is applied to all sequence pairs and the pair-wise results combined in a simple multiple sequence alignment program. From this alignment, further constraints are selected to bias the low-level alignments in the DDP algorithm and the process iterated. The results, however, showed that this overall iteration was not needed and one-pass gave results at least as good as the 'standard' progressive method of multiple sequence alignment. Further applications of the method are discussed.

Algorithms↗

PubMed2002

Exon discovery by genomic sequence alignment.

MOTIVATION: During evolution, functional regions in genomic sequences tend to be more highly conserved than randomly mutating 'junk DNA' so local sequence similarity often indicates biological functionality. This fact can be used to identify functional elements in large eukaryotic DNA sequences by cross-species sequence comparison. In recent years, several gene-prediction methods have been proposed that work by comparing anonymous genomic sequences, for example from human and mouse. The main advantage of these methods is that they are based on simple and generally applicable measures of (local) sequence similarity; unlike standard gene-finding approaches they do not depend on species-specific training data or on the presence of cognate genes in data bases. As all comparative sequence-analysis methods, the new comparative gene-finding approaches critically rely on the quality of the underlying sequence alignments. RESULTS: Herein, we describe a new implementation of the sequence-alignment program DIALIGN that has been developed for alignment of large genomic sequences. We compare our method to the alignment programs PipMaker, WABA and BLAST and we show that local similarities identified by these programs are highly correlated to protein-coding regions. In our test runs, PipMaker was the most sensitive method while DIALIGN was most specific. AVAILABILITY: The program is downloadable from the DIALIGN home page at http://bibiserv.techfak.uni-bielefeld.de/dialign/.

Animals↗

PubMed1998

Domain identification by clustering sequence alignments.

MOTIVATION: As sequence databases grow rapidly, results from sequence comparison searches using fast search methods such as BLAST and FASTA tend to be long and difficult to digest. RESULTS: In this paper, we present a new method to extract domain information from sequence comparison searches by clustering the resulting alignments according to their similarity to the query sequence. Efficient tree structures and algorithms are used to organize the alignment data such that structurally conserved elements can be easily identified. The hierarchical nature of the data structures used and the flexible X-Window-based interface provide an efficient and intuitive means to explore the alignment data at different levels so that the common domains, as well as distantly related features, can be explored. AVAILABILITY: The clustering program is available by anonymous ftp at: ftp.embl-ebi.ac.uk under directory /pub/software/unix, file: clustering.tar.Z.

Cluster Analysis↗

PubMed1989

A multiple sequence alignment algorithm for homologous proteins using secondary structure information and optionally keying alignments to functionally important sites.

The programs described herein function as part of a suite of programs designed for pairwise alignment, multiple alignment, generation of randomized sequences, production of alignment scores and a sorting routine for analysis of the alignments produced. The sequence alignment programs penalize gaps (absences of residues) within regions of protein secondary structure and have the added option of 'fingerprinting' structurally or functionally important protein-residues. The multiple alignment program is based upon the sequence alignment method of Needleman and Wunsch and the multiple alignment extension of Barton and Sternberg. Our application includes the feature of optionally weighting active site, monomer--monomer, ligand contact or other important template residues to bias the alignment toward matching these residues. A sum-score for the alignments is introduced, which is independent of gap penalties. This score more adequately reflects the character of the alignments for a given scoring matrix than the gap-penalty-dependent total score described previously in the literature. In addition, individual amino acid similarity scores at each residue position in the alignments are printed with the alignment output to enable immediate quantitative assessment of homology at key sections of the aligned chains.

Algorithms↗

PubMed2004

On the significance of sequence alignments when using multiple scoring matrices.

MOTIVATION: Pairwise local sequence alignment is commonly used to search data bases for sequences related to some query sequence. Alignments are obtained using a scoring matrix that takes into account the different frequencies of occurrence of the various types of amino acid substitutions. Software like BLAST provides the user with a set of scoring matrices available to choose from, and in the literature it is sometimes recommended to try several scoring matrices on the sequences of interest. The significance of an alignment is usually assessed by looking at E-values and p-values. While sequence lengths and data base sizes enter the standard calculations of significance, it is much less common to take the use of several scoring matrices on the same sequences into account. Altschul proposed corrections of the p-value that account for the simultaneous use of an infinite number of PAM matrices. Here we consider the more realistic situation where the user may choose from a finite set of popular PAM and BLOSUM matrices, in particular the ones available in BLAST. It turns out that the significance of a result can be considerably overestimated, if a set of substitution matrices is used in an alignment problem and the most significant alignment is then quoted. RESULTS: Based on extensive simulations, we study the multiple testing problem that occurs when several scoring matrices for local sequence alignment are used. We consider a simple Bonferroni correction of the p-values and investigate its accuracy. Finally, we propose a more accurate correction based on extreme value distributions fitted to the maximum of the normalized scores obtained from different scoring matrices. For various sets of matrices we provide correction factors which can be easily applied to adjust p- and E-values reported by software packages.

Data Interpretation, Statistical↗

PubMed1995

Elision: a method for accommodating multiple molecular sequence alignments with alignment-ambiguous sites.

The process of multiple sequence alignment provides homology statements for the phylogenetic analysis of molecular data. Unfortunately, multiple alignments are frequently nonunique. Two sources of these multiple alignments are analysis based on different sets of alignment parameter values (gap:change cost ratios) and nonunique equally costly alignments based on a single set of alignment parameters. By "eliding" these individual alignments into a single grand alignment, phylogeny that is weighted toward those positions that align more consistently can be reconstructed. Positions that show greater variation among alignments will be relatively downweighted. The technique results in a weighting procedure that is a posteriori and based on the evidence established from the original sequence alignments.

Alligators and Crocodiles↗