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Suboptimal sequence alignment in molecular biology. Alignment with error analysis.

A molecular sequence alignment algorithm based on dynamic programming has been extended to allow the computation of all pairs of residues that can be part of optimal and suboptimal sequence alignments. The uncertainties inherent in sequence alignment can be displayed using a new form of dot plot. The method allows the qualitative assessment of whether or not two sequences are related, and can reveal what parts of the alignment are better determined than others. It also permits the computation of representative optimal and suboptimal alignments. The relation between alignment reliability and alignment parameters is discussed. Other applications are to cyclical permutations of sequences and the detection of self-similarity. An application to multiple sequence alignment is noted.

Algorithms↗

Functionally important residues of aromatic L-amino acid decarboxylase probed by sequence alignment and site-directed mutagenesis.

To identify functional residues of rat liver L-aromatic amino acid decarboxylase (AADC), we aligned the sequences of 13 group II amino acid decarboxylases and performed mutational analysis on the residues that were invariant or conservatively substituted. Replacements of His192, Asp252, Asp271, Ser296, Lys303, Tyr332, and Arg355 with alanine residues decreased the AADC activity (kcat/K(m)) by more than 10(4)-fold. Conservative replacements of [Asp252-->Glu], [Lys303-->Arg], and [Tyr332-->Phe] also resulted in decreases in activity by more than 10(4)-fold, indicating that both the chemical properties and the shape of these residues are essential for catalysis. The presence of a Schiff base between the amino group of Lys303 and the coenzyme pyridoxal 5'-phosphate is important for catalysis, probably at the transaldimination step. The enzyme activity was essentially unaffected by conservative mutation of [Arg355-->Lys], showing that the presence of a basic group at position 355 is necessary and sufficient for the catalysis. Replacement of [Thr246-->Ala], [His269-->Ala], and [Trp363-->Leu] yielded mutant enzymes that were 1-8% as active as the wild-type enzyme; these residues are not essential for the catalysis but are considered to contribute to the activity through conformational or other effects. The roles of the catalytically important residues of the group II amino acid decarboxylases probed in this study were discussed in the light of their relationship with the residues of other pyridoxal enzymes.

Amino Acid Sequence↗

A space-efficient algorithm for the constrained pairwise sequence alignment problem.

The constrained pairwise sequence alignment (CPSA) problem aims to align two given sequences by aligning their similar subsequences in the same region under the guidance of a given pattern (constraint). Let the lengths of the sequences be m, and n where n <or= m, and let r <or= n be the length of the given pattern. The optimum constrained pairwise alignment score can be computed using O(rn) space by a naive dynamic programming solution. If an optimal alignment path is desired then the space requirement of the naive dynamic programming algorithm is O(rnm). There is a divide-and-conquer algorithm that reduces the memory requirement of finding an optimal alignment for the CPSA problem to O(rn). In this paper, we present a space-efficient CPSA algorithm that returns an optimal alignment. Our analysis on real protein sequences suggests that our algorithm requires only O(n) space in practice. This algorithm is not only space efficient but also very fast. A generalization of the CPSA problem for multiple sequences is called the constrained multiple sequence alignment (CMSA) problem. Our CPSA algorithm also improves the space requirement of progressive CMSA algorithms that use solutions of CPSA problems.

Algorithms↗

Parallel sequence alignment in limited space.

Sequence comparison with affine gap costs is a problem that is readily parallelizable on simple single-instruction, multiple-data stream (SIMD) parallel processors using only constant space per processing element. Unfortunately, the twin problem of sequence alignment, finding the optimal character-by-character correspondence between two sequences, is more complicated. While the innovative O(n2)-time and O(n)-space serial algorithm has been parallelized for multiple-instruction, multiple-data stream (MIMD) computers with only a communication-time slowdown, typically O(log n), it is not suitable for hardware-efficient SIMD parallel processors with only local communication. This paper proposes several methods of computing sequence alignments with limited memory per processing element. The algorithms are also well-suited to serial implementation. The simpler algorithms feature, for an arbitrary integer L, a factor of L slowdown in exchange for reducing space requirements from O(n) to O(L square root of n) per processing element. Using this result, we describe an O(n log n) parallel time algorithm that requires O(log n) space per processing element on O(n) SIMD processing elements with only a mesh or linear interconnection network.

Algorithms↗

MAFFT version 5: improvement in accuracy of multiple sequence alignment.

The accuracy of multiple sequence alignment program MAFFT has been improved. The new version (5.3) of MAFFT offers new iterative refinement options, H-INS-i, F-INS-i and G-INS-i, in which pairwise alignment information are incorporated into objective function. These new options of MAFFT showed higher accuracy than currently available methods including TCoffee version 2 and CLUSTAL W in benchmark tests consisting of alignments of >50 sequences. Like the previously available options, the new options of MAFFT can handle hundreds of sequences on a standard desktop computer. We also examined the effect of the number of homologues included in an alignment. For a multiple alignment consisting of approximately 8 sequences with low similarity, the accuracy was improved (2-10 percentage points) when the sequences were aligned together with dozens of their close homologues (E-value < 10(-5)-10(-20)) collected from a database. Such improvement was generally observed for most methods, but remarkably large for the new options of MAFFT proposed here. Thus, we made a Ruby script, mafftE.rb, which aligns the input sequences together with their close homologues collected from SwissProt using NCBI-BLAST.

Reproducibility of Results↗

Optimization of multiple-sequence alignment based on multiple-structure alignment.

Routinely used multiple-sequence alignment methods use only sequence information. Consequently, they may produce inaccurate alignments. Multiple-structure alignment methods, on the other hand, optimize structural alignment by ignoring sequence information. Here, we present an optimization method that unifies sequence and structure information. The alignment score is based on standard amino acid substitution probabilities combined with newly computed three-dimensional structure alignment probabilities. The advantage of our alignment scheme is in its ability to produce more accurate multiple alignments. We demonstrate the usefulness of the method in three applications: 1) computing more accurate multiple-sequence alignments, 2) analyzing protein conformational changes, and 3) computation of amino acid structure-sequence conservation with application to protein-protein docking prediction. The method is available at http://bioinfo3d.cs.tau.ac.il/staccato/.

Amino Acid Sequence↗

EMBL-Align: a new public nucleotide and amino acid multiple sequence alignment database.

UNLABELLED: The submission of multiple sequence alignment data to EMBL has grown 30-fold in the past 10 years, creating a problem of archiving them. The EBI has developed a new public database of multiple sequence alignments called EMBL-Align. It has a dedicated web-based submission tool, Webin-Align. Together they represent a comprehensive data management solution for alignment data. Webin-Align accepts all the common alignment formats and can display data in CLUSTALW format as well as a new standard EMBL-Align flat file format. The alignments are stored in the EMBL-Align database and can be queried from the EBI SRS (Sequence Retrieval System) server. AVAILABILITY: Webin-Align: http://www.ebi.ac.uk/embl/Submission/align_top.html, EMBL-Align: ftp://ftp.ebi.ac.uk/pub/databases/embl/align, http://srs.ebi.ac.uk/

Amino Acid Sequence↗

COFFEE: an objective function for multiple sequence alignments.

MOTIVATION: In order to increase the accuracy of multiple sequence alignments, we designed a new strategy for optimizing multiple sequence alignments by genetic algorithm. We named it COFFEE (Consistency based Objective Function For alignmEnt Evaluation). The COFFEE score reflects the level of consistency between a multiple sequence alignment and a library containing pairwise alignments of the same sequences. RESULTS: We show that multiple sequence alignments can be optimized for their COFFEE score with the genetic algorithm package SAGA. The COFFEE function is tested on 11 test cases made of structural alignments extracted from 3D_ali. These alignments are compared to those produced using five alternative methods. Results indicate that COFFEE outperforms the other methods when the level of identity between the sequences is low. Accuracy is evaluated by comparison with the structural alignments used as references. We also show that the COFFEE score can be used as a reliability index on multiple sequence alignments. Finally, we show that given a library of structure-based pairwise sequence alignments extracted from FSSP, SAGA can produce high-quality multiple sequence alignments. The main advantage of COFFEE is its flexibility. With COFFEE, any method suitable for making pairwise alignments can be extended to making multiple alignments. AVAILABILITY: The package is available along with the test cases through the WWW: http://www. ebi.ac.uk/cedric CONTACT: cedric.notredame@ebi.ac.uk

Algorithms↗

State of the art: refinement of multiple sequence alignments.

BACKGROUND: Accurate multiple sequence alignments of proteins are very important in computational biology today. Despite the numerous efforts made in this field, all alignment strategies have certain shortcomings resulting in alignments that are not always correct. Refinement of existing alignment can prove to be an intelligent choice considering the increasing importance of high quality alignments in large scale high-throughput analysis. RESULTS: We provide an extensive comparison of the performance of the alignment refinement algorithms. The accuracy and efficiency of the refinement programs are compared using the 3D structure-based alignments in the BAliBASE benchmark database as well as manually curated high quality alignments from Conserved Domain Database (CDD). CONCLUSION: Comparison of performance for refined alignments revealed that despite the absence of dramatic improvements, our refinement method, REFINER, which uses conserved regions as constraints performs better in improving the alignments generated by different alignment algorithms. In most cases REFINER produces a higher-scoring, modestly improved alignment that does not deteriorate the well-conserved regions of the original alignment.

Algorithms↗

Multiple sequence alignment with hierarchical clustering.

An algorithm is presented for the multiple alignment of sequences, either proteins or nucleic acids, that is both accurate and easy to use on microcomputers. The approach is based on the conventional dynamic-programming method of pairwise alignment. Initially, a hierarchical clustering of the sequences is performed using the matrix of the pairwise alignment scores. The closest sequences are aligned creating groups of aligned sequences. Then close groups are aligned until all sequences are aligned in one group. The pairwise alignments included in the multiple alignment form a new matrix that is used to produce a hierarchical clustering. If it is different from the first one, iteration of the process can be performed. The method is illustrated by an example: a global alignment of 39 sequences of cytochrome c.

Algorithms↗

3DCoffee: combining protein sequences and structures within multiple sequence alignments.

Most bioinformatics analyses require the assembly of a multiple sequence alignment. It has long been suspected that structural information can help to improve the quality of these alignments, yet the effect of combining sequences and structures has not been evaluated systematically. We developed 3DCoffee, a novel method for combining protein sequences and structures in order to generate high-quality multiple sequence alignments. 3DCoffee is based on TCoffee version 2.00, and uses a mixture of pairwise sequence alignments and pairwise structure comparison methods to generate multiple sequence alignments. We benchmarked 3DCoffee using a subset of HOMSTRAD, the collection of reference structural alignments. We found that combining TCoffee with the threading program Fugue makes it possible to improve the accuracy of our HOMSTRAD dataset by four percentage points when using one structure only per dataset. Using two structures yields an improvement of ten percentage points. The measures carried out on HOM39, a HOMSTRAD subset composed of distantly related sequences, show a linear correlation between multiple sequence alignment accuracy and the ratio of number of provided structure to total number of sequences. Our results suggest that in the case of distantly related sequences, a single structure may not be enough for computing an accurate multiple sequence alignment.

Protein Conformation↗

RASCAL: rapid scanning and correction of multiple sequence alignments.

MOTIVATION: Most multiple sequence alignment programs use heuristics that sometimes introduce errors into the alignment. The most commonly used methods to correct these errors use iterative techniques to maximize an objective function. We present here an alternative, knowledge-based approach that combines a number of recently developed methods into a two-step refinement process. The alignment is divided horizontally and vertically to form a 'lattice' in which well aligned regions can be differentiated. Alignment correction is then restricted to the less reliable regions, leading to a more reliable and efficient refinement strategy. RESULTS: The accuracy and reliability of RASCAL is demonstrated using: (i) alignments from the BAliBASE benchmark database, where significant improvements were often observed, with no deterioration of the existing high-quality regions, (ii) a large scale study involving 946 alignments from the ProDom protein domain database, where alignment quality was increased in 68% of the cases; and (iii) an automatic pipeline to obtain a high-quality alignment of 695 full-length nuclear receptor proteins, which took 11 min on a DEC Alpha 6100 computer AVAILABILITY: RASCAL is available at ftp://ftp-igbmc.u-strasbg.fr/pub/RASCAL. SUPPLEMENTARY INFORMATION: http://bioinfo-igbmc.u-strasbourg.fr/BioInfo/RASCAL/paper/rascal_supp.html

Algorithms↗

MALIGNED: a multiple sequence alignment editor.

A multiple sequence alignment editor is described which runs on a VAX/VMS system and can exchange data with a number of other programs, including those of the Genetics Computer Group (GCG). Up to 199 sequences can be aligned. The quality of the alignment can be easily judged during its development because the display attributes to each character are determined by the way it matches the other sequences. Four methods are available for calculating the highlighting to emphasize different aspects of the relationships of the sequences and up to four styles of highlighting can be used at the same time. Laser printer output is suitable for publication without modification.

Molecular Sequence Data↗

AL2CO: calculation of positional conservation in a protein sequence alignment.

MOTIVATION: Amino acid sequence alignments are widely used in the analysis of protein structure, function and evolutionary relationships. Proteins within a superfamily usually share the same fold and possess related functions. These structural and functional constraints are reflected in the alignment conservation patterns. Positions of functional and/or structural importance tend to be more conserved. Conserved positions are usually clustered in distinct motifs surrounded by sequence segments of low conservation. Poorly conserved regions might also arise from the imperfections in multiple alignment algorithms and thus indicate possible alignment errors. Quantification of conservation by attributing a conservation index to each aligned position makes motif detection more convenient. Mapping these conservation indices onto a protein spatial structure helps to visualize spatial conservation features of the molecule and to predict functionally and/or structurally important sites. Analysis of conservation indices could be a useful tool in detection of potentially misaligned regions and will aid in improvement of multiple alignments. RESULTS: We developed a program to calculate a conservation index at each position in a multiple sequence alignment using several methods. Namely, amino acid frequencies at each position are estimated and the conservation index is calculated from these frequencies. We utilize both unweighted frequencies and frequencies weighted using two different strategies. Three conceptually different approaches (entropy-based, variance-based and matrix score-based) are implemented in the algorithm to define the conservation index. Calculating conservation indices for 35522 positions in 284 alignments from SMART database we demonstrate that different methods result in highly correlated (correlation coefficient more than 0.85) conservation indices. Conservation indices show statistically significant correlation between sequentially adjacent positions i and i + j, where j < 13, and averaging of the indices over the window of three positions is optimal for motif detection. Positions with gaps display substantially lower conservation properties. We compare conservation properties of the SMART alignments or FSSP structural alignments to those of the ClustalW alignments. The results suggest that conservation indices should be a valuable tool of alignment quality assessment and might be used as an objective function for refinement of multiple alignments. AVAILABILITY: The C code of the AL2CO program and its pre-compiled versions for several platforms as well as the details of the analysis are freely available at ftp://iole.swmed.edu/pub/al2co/.

Algorithms↗

SQUARE--determining reliable regions in sequence alignments.

The Server for Quick Alignment Reliability Evaluation (SQUARE) is a Web-based version of the method we developed to predict regions of reliably aligned residues in sequence alignments. Given an alignment between a query sequence and a sequence of known structure, SQUARE is able to predict which residues are reliably aligned. The server accesses a database of profiles of sequences of known three-dimensional structures in order to calculate the scores for each residue in the alignment. SQUARE produces a graphical output of the residue profile-derived alignment scores along with an indication of the reliability of the alignment. In addition, the scores can be compared against template secondary structure, conserved residues and important sites.

Algorithms↗

An exact solution for the segment-to-segment multiple sequence alignment problem.

MOTIVATION: In molecular biology, sequence alignment is a crucial tool in studying the structure and function of molecules, as well as the evolution of species. In the segment-to-segment variation of the multiple alignment problem, the input can be seen as a set of non-gapped segment pairs (diagonals). Given a weight function that assigns a weight score to every possible diagonal, the goal is to choose a consistent set of diagonals of maximum weight. We show that the segment-to-segment multiple alignment problem is equivalent to a novel formulation of the Maximum Trace problem: the Generalized Maximum Trace (GMT) problem. Solving this problem to optimality, therefore, may improve upon the previous greedy strategies that are used for solving the segment-to-segment multiple sequence alignment problem. We show that the GMT can be stated in terms of an integer linear program and then solve the integer linear program using methods from polyhedral combinatorics. This leads to a branch-and-cut algorithm for segment-to-segment multiple sequence alignment. RESULTS: We report on our first computational experiences with this novel method and show that the program is able to find optimal solutions for real-world test examples.

Algorithms↗

APDB: a web server to evaluate the accuracy of sequence alignments using structural information.

UNLABELLED: The APDB webserver uses structural information to evaluate the alignment of sequences with known structures. It returns a score correlated to the overall alignment accuracy as well as a local evaluation. Any sequence alignment can be analyzed with APDB provided it includes at least two proteins with known structures. Sequences without a known structure are simply ignored and do not contribute to the scoring procedure. AVAILABILITY: APDB is part of the T-Coffee suite of tools for alignment analysis, it is available on www.tcoffee.org. A stand-alone version of the package is also available as a freeware open source from the same address.

Algorithms↗

A method for multiple sequence alignment with gaps.

A method that performs multiple sequence alignment by cyclical use of the standard pairwise Needleman-Wunsch algorithm is presented. The required central processor unit time is of the same order of magnitude as the standard Needleman-Wunsch pairwise implementation. Comparison with the one known case where the optimal multiple sequence alignment has been rigorously determined shows that in practice the proposed method finds the mathematically optimal solution. The more interesting question of the biological usefulness of such multiple sequence alignment over pairwise approaches is assessed using protein families whose X-ray structures are known. The two such cases studied, the subdomains of the ricin B-chain and the S-domains of virus coat proteins, have low pairwise similarity and thus fail to align correctly under standard pairwise sequence comparison. In both cases the multiple sequence alignment produced by the proposed technique, apart from minor deviations at loop regions, correctly predicts the true structural alignment. Thus, given many sequences of low pairwise similarity, the proposed multiple sequence method, can extract any familial similarity and so produce a sequence alignment consistent with the underlying structural homology.

Algorithms↗