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Carroll H, Beckstead W, O'Connor T, Ebbert M, Clement M, Snell Q, McClellan D. DNA reference alignment benchmarks based on tertiary structure of encoded proteins. Bioinformatics 2007; 23:2648-9. [PMID: 17686799 DOI: 10.1093/bioinformatics/btm389] [Citation(s) in RCA: 45] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Multiple sequence alignments (MSAs) are at the heart of bioinformatics analysis. Recently, a number of multiple protein sequence alignment benchmarks (i.e. BAliBASE, OXBench, PREFAB and SMART) have been released to evaluate new and existing MSA applications. These databases have been well received by researchers and help to quantitatively evaluate MSA programs on protein sequences. Unfortunately, analogous DNA benchmarks are not available, making evaluation of MSA programs difficult for DNA sequences. RESULTS This work presents the first known multiple DNA sequence alignment benchmarks that are (1) comprised of protein-coding portions of DNA (2) based on biological features such as the tertiary structure of encoded proteins. These reference DNA databases contain a total of 3545 alignments, comprising of 68 581 sequences. Two versions of the database are available: mdsa_100s and mdsa_all. The mdsa_100s version contains the alignments of the data sets that TBLASTN found 100% sequence identity for each sequence. The mdsa_all version includes all hits with an E-value score above the threshold of 0.001. A primary use of these databases is to benchmark the performance of MSA applications on DNA data sets. The first such case study is included in the Supplementary Material.
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Affiliation(s)
- Hyrum Carroll
- Computer Science Department, Brigham Young University, Provo, Utah 84602, USA.
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102
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Yard BA, Carter LG, Johnson KA, Overton IM, Dorward M, Liu H, McMahon SA, Oke M, Puech D, Barton GJ, Naismith JH, Campopiano DJ. The Structure of Serine Palmitoyltransferase; Gateway to Sphingolipid Biosynthesis. J Mol Biol 2007; 370:870-86. [PMID: 17559874 DOI: 10.1016/j.jmb.2007.04.086] [Citation(s) in RCA: 109] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2007] [Revised: 04/12/2007] [Accepted: 04/18/2007] [Indexed: 11/19/2022]
Abstract
Sphingolipid biosynthesis commences with the condensation of L-serine and palmitoyl-CoA to produce 3-ketodihydrosphingosine (KDS). This reaction is catalysed by the PLP-dependent enzyme serine palmitoyltransferase (SPT; EC 2.3.1.50), which is a membrane-bound heterodimer (SPT1/SPT2) in eukaryotes such as humans and yeast and a cytoplasmic homodimer in the Gram-negative bacterium Sphingomonas paucimobilis. Unusually, the outer membrane of S. paucimobilis contains glycosphingolipid (GSL) instead of lipopolysaccharide (LPS), and SPT catalyses the first step of the GSL biosynthetic pathway in this organism. We report here the crystal structure of the holo-form of S. paucimobilis SPT at 1.3 A resolution. The enzyme is a symmetrical homodimer with two active sites and a monomeric tertiary structure consisting of three domains. The PLP cofactor is bound covalently to a lysine residue (Lys265) as an internal aldimine/Schiff base and the active site is composed of residues from both subunits, located at the bottom of a deep cleft. Models of the human SPT1/SPT2 heterodimer were generated from the bacterial structure by bioinformatics analysis. Mutations in the human SPT1-encoding subunit have been shown to cause a neuropathological disease known as hereditary sensory and autonomic neuropathy type I (HSAN1). Our models provide an understanding of how these mutations may affect the activity of the enzyme.
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Affiliation(s)
- Beverley A Yard
- School of Chemistry, EaStCHEM, The University of Edinburgh, West Mains Road, Edinburgh, EH9 3JJ, Scotland, UK
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103
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Moretti S, Armougom F, Wallace IM, Higgins DG, Jongeneel CV, Notredame C. The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods. Nucleic Acids Res 2007; 35:W645-8. [PMID: 17526519 PMCID: PMC1933118 DOI: 10.1093/nar/gkm333] [Citation(s) in RCA: 168] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.
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Affiliation(s)
- Sebastien Moretti
- Swiss Institute of Bioinformatics, Bâtiment Génopode, UNIL, CH-101 Lausanne, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland and Information Génomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM), Parc Scientifique de Luminy, 163 Avenue de Luminy, FR- 13288, Marseille cedex 09, France
| | - Fabrice Armougom
- Swiss Institute of Bioinformatics, Bâtiment Génopode, UNIL, CH-101 Lausanne, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland and Information Génomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM), Parc Scientifique de Luminy, 163 Avenue de Luminy, FR- 13288, Marseille cedex 09, France
| | - Iain M. Wallace
- Swiss Institute of Bioinformatics, Bâtiment Génopode, UNIL, CH-101 Lausanne, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland and Information Génomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM), Parc Scientifique de Luminy, 163 Avenue de Luminy, FR- 13288, Marseille cedex 09, France
| | - Desmond G. Higgins
- Swiss Institute of Bioinformatics, Bâtiment Génopode, UNIL, CH-101 Lausanne, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland and Information Génomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM), Parc Scientifique de Luminy, 163 Avenue de Luminy, FR- 13288, Marseille cedex 09, France
| | - Cornelius V. Jongeneel
- Swiss Institute of Bioinformatics, Bâtiment Génopode, UNIL, CH-101 Lausanne, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland and Information Génomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM), Parc Scientifique de Luminy, 163 Avenue de Luminy, FR- 13288, Marseille cedex 09, France
| | - Cedric Notredame
- Swiss Institute of Bioinformatics, Bâtiment Génopode, UNIL, CH-101 Lausanne, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland and Information Génomique et Structurale, CNRS UPR2589, Institute for Structural Biology and Microbiology (IBSM), Parc Scientifique de Luminy, 163 Avenue de Luminy, FR- 13288, Marseille cedex 09, France
- *To whom correspondence should be addressed. +33 491 106 486 +33 491 106 489
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104
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Chikkagoudar S, Roshan U, Livesay D. eProbalign: generation and manipulation of multiple sequence alignments using partition function posterior probabilities. Nucleic Acids Res 2007; 35:W675-7. [PMID: 17485479 PMCID: PMC1933135 DOI: 10.1093/nar/gkm267] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Probalign computes maximal expected accuracy multiple sequence alignments from partition function posterior probabilities. To date, Probalign is among the very best scoring methods on the BAliBASE, HOMSTRAD and OXBENCH benchmarks. Here, we introduce eProbalign, which is an online implementation of the approach. Moreover, the eProbalign web server doubles as an online platform for post-alignment analysis. The heart-and-soul of the post-alignment functionality is the Probalign Alignment Viewer applet, which provides users a convenient means to manipulate the alignments by posterior probabilities. The viewer can also be used to produce graphical and text versions of the output. The eProbalign web server and underlying Probalign source code is freely accessible at http://probalign.njit.edu
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Affiliation(s)
- Satish Chikkagoudar
- Department of Computer Science, New Jersey Institute of Technology and Department of Computer Science and Bioinformatics Research Center, University of North Carolina at Charlotte
| | - Usman Roshan
- Department of Computer Science, New Jersey Institute of Technology and Department of Computer Science and Bioinformatics Research Center, University of North Carolina at Charlotte
- *To whom correspondence should be addressed. +1-973-596-2872+1-973-596-5777
| | - Dennis Livesay
- Department of Computer Science, New Jersey Institute of Technology and Department of Computer Science and Bioinformatics Research Center, University of North Carolina at Charlotte
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105
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Wilm A, Mainz I, Steger G. An enhanced RNA alignment benchmark for sequence alignment programs. Algorithms Mol Biol 2006; 1:19. [PMID: 17062125 PMCID: PMC1635699 DOI: 10.1186/1748-7188-1-19] [Citation(s) in RCA: 98] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2006] [Accepted: 10/24/2006] [Indexed: 11/10/2022] Open
Abstract
Background The performance of alignment programs is traditionally tested on sets of protein sequences, of which a reference alignment is known. Conclusions drawn from such protein benchmarks do not necessarily hold for the RNA alignment problem, as was demonstrated in the first RNA alignment benchmark published so far. For example, the twilight zone – the similarity range where alignment quality drops drastically – starts at 60 % for RNAs in comparison to 20 % for proteins. In this study we enhance the previous benchmark. Results The RNA sequence sets in the benchmark database are taken from an increased number of RNA families to avoid unintended impact by using only a few families. The size of sets varies from 2 to 15 sequences to assess the influence of the number of sequences on program performance. Alignment quality is scored by two measures: one takes into account only nucleotide matches, the other measures structural conservation. The performance order of parameters – like nucleotide substitution matrices and gap-costs – as well as of programs is rated by rank tests. Conclusion Most sequence alignment programs perform equally well on RNA sequence sets with high sequence identity, that is with an average pairwise sequence identity (APSI) above 75 %. Parameters for gap-open and gap-extension have a large influence on alignment quality lower than APSI ≤ 75 %; optimal parameter combinations are shown for several programs. The use of different 4 × 4 substitution matrices improved program performance only in some cases. The performance of iterative programs drastically increases with increasing sequence numbers and/or decreasing sequence identity, which makes them clearly superior to programs using a purely non-iterative, progressive approach. The best sequence alignment programs produce alignments of high quality down to APSI > 55 %; at lower APSI the use of sequence+structure alignment programs is recommended.
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Affiliation(s)
- Andreas Wilm
- Institut für Physikalische Biologie, Heinrich-Heine-Universität Düsseldorf, Universitätsstr. 1, 40225 Düsseldorf, Germany
| | - Indra Mainz
- Institut für Physikalische Biologie, Heinrich-Heine-Universität Düsseldorf, Universitätsstr. 1, 40225 Düsseldorf, Germany
| | - Gerhard Steger
- Institut für Physikalische Biologie, Heinrich-Heine-Universität Düsseldorf, Universitätsstr. 1, 40225 Düsseldorf, Germany
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106
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Raghava GPS, Barton GJ. Quantification of the variation in percentage identity for protein sequence alignments. BMC Bioinformatics 2006; 7:415. [PMID: 16984632 PMCID: PMC1592310 DOI: 10.1186/1471-2105-7-415] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2005] [Accepted: 09/19/2006] [Indexed: 11/26/2022] Open
Abstract
Background Percentage Identity (PID) is frequently quoted in discussion of sequence alignments since it appears simple and easy to understand. However, although there are several different ways to calculate percentage identity and each may yield a different result for the same alignment, the method of calculation is rarely reported. Accordingly, quantification of the variation in PID caused by the different calculations would help in interpreting PID values in the literature. In this study, the variation in PID was quantified systematically on a reference set of 1028 alignments generated by comparison of the protein three-dimensional structures. Since the alignment algorithm may also affect the range of PID, this study also considered the effect of algorithm, and the combination of algorithm and PID method. Results The maximum variation in PID due to the calculation method was 11.5% while the effect of alignment algorithm on PID was up to 14.6% across three popular alignment methods. The combined effect of alignment algorithm and PID calculation gave a variation of up to 22% on the test data, with an average of 5.3% ± 2.8% for sequence pairs with < 30% identity. In order to see which PID method was most highly correlated with structural similarity, four different PID calculations were compared to similarity scores (Sc) from the comparison of the corresponding protein three-dimensional structures. The highest correlation coefficient for a PID calculation was 0.80. In contrast, the more sophisticated Z-score calculated by reference to randomized sequences gave a correlation coefficient of 0.84. Conclusion Although it is well known amongst expert sequence analysts that PID is a poor score for discriminating between protein sequences, the apparent simplicity of the percentage identity score encourages its widespread use in establishing cutoffs for structural similarity. This paper illustrates that not only is PID a poor measure of sequence similarity when compared to the Z-score, but that there is also a large uncertainty in reported PID values. Since better alternatives to PID exist to quantify sequence similarity, these should be quoted where possible in preference to PID. The findings presented here should prove helpful to those new to sequence analysis, and in warning those who seek to interpret the value of a PID reported in the literature.
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Affiliation(s)
- GPS Raghava
- Bioinformatics Centre, Institute of Microbial Technology, Sector 39A, Chandigarh, India
- This work was intitated when both authors were at the University of Oxford, Laboratory of Molecular Biophysics, Rex Richards Building, Oxford, OX1 3QU, UK
| | - Geoffrey J Barton
- School of Life Sciences Research, University of Dundee, Dow Street, Dundee, DD1 5EH, Scotland, UK
- This work was intitated when both authors were at the University of Oxford, Laboratory of Molecular Biophysics, Rex Richards Building, Oxford, OX1 3QU, UK
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107
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Roshan U, Livesay DR. Probalign: multiple sequence alignment using partition function posterior probabilities. Bioinformatics 2006; 22:2715-21. [PMID: 16954142 DOI: 10.1093/bioinformatics/btl472] [Citation(s) in RCA: 143] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
MOTIVATION The maximum expected accuracy optimization criterion for multiple sequence alignment uses pairwise posterior probabilities of residues to align sequences. The partition function methodology is one way of estimating these probabilities. Here, we combine these two ideas for the first time to construct maximal expected accuracy sequence alignments. RESULTS We bridge the two techniques within the program Probalign. Our results indicate that Probalign alignments are generally more accurate than other leading multiple sequence alignment methods (i.e. Probcons, MAFFT and MUSCLE) on the BAliBASE 3.0 protein alignment benchmark. Similarly, Probalign also outperforms these methods on the HOMSTRAD and OXBENCH benchmarks. Probalign ranks statistically highest (P-value < 0.005) on all three benchmarks. Deeper scrutiny of the technique indicates that the improvements are largest on datasets containing N/C-terminal extensions and on datasets containing long and heterogeneous length proteins. These points are demonstrated on both real and simulated data. Finally, our method also produces accurate alignments on long and heterogeneous length datasets containing protein repeats. Here, alignment accuracy scores are at least 10% and 15% higher than the other three methods when standard deviation of length is >300 and 400, respectively. AVAILABILITY Open source code implementing Probalign as well as for producing the simulated data, and all real and simulated data are freely available from http://www.cs.njit.edu/usman/probalign
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Affiliation(s)
- Usman Roshan
- Department of Computer Science, New Jersey Institute of Technology GITC 4400, University Heights, NJ 07102, USA.
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108
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Thompson JD, Koehl P, Ripp R, Poch O. BAliBASE 3.0: latest developments of the multiple sequence alignment benchmark. Proteins 2006; 61:127-36. [PMID: 16044462 DOI: 10.1002/prot.20527] [Citation(s) in RCA: 224] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Multiple sequence alignment is one of the cornerstones of modern molecular biology. It is used to identify conserved motifs, to determine protein domains, in 2D/3D structure prediction by homology and in evolutionary studies. Recently, high-throughput technologies such as genome sequencing and structural proteomics have lead to an explosion in the amount of sequence and structure information available. In response, several new multiple alignment methods have been developed that improve both the efficiency and the quality of protein alignments. Consequently, the benchmarks used to evaluate and compare these methods must also evolve. We present here the latest release of the most widely used multiple alignment benchmark, BAliBASE, which provides high quality, manually refined, reference alignments based on 3D structural superpositions. Version 3.0 of BAliBASE includes new, more challenging test cases, representing the real problems encountered when aligning large sets of complex sequences. Using a novel, semiautomatic update protocol, the number of protein families in the benchmark has been increased and representative test cases are now available that cover most of the protein fold space. The total number of proteins in BAliBASE has also been significantly increased from 1444 to 6255 sequences. In addition, full-length sequences are now provided for all test cases, which represent difficult cases for both global and local alignment programs. Finally, the BAliBASE Web site (http://www-bio3d-igbmc.u-strasbg.fr/balibase) has been completely redesigned to provide a more user-friendly, interactive interface for the visualization of the BAliBASE reference alignments and the associated annotations.
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Affiliation(s)
- Julie D Thompson
- Département de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Molculaire et Cellulaire, (CNRS/INSERM/ULP), Illkirch Cedex, France.
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109
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Edgar RC, Batzoglou S. Multiple sequence alignment. Curr Opin Struct Biol 2006; 16:368-73. [PMID: 16679011 DOI: 10.1016/j.sbi.2006.04.004] [Citation(s) in RCA: 202] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2006] [Revised: 03/22/2006] [Accepted: 04/27/2006] [Indexed: 10/24/2022]
Abstract
Multiple sequence alignments are an essential tool for protein structure and function prediction, phylogeny inference and other common tasks in sequence analysis. Recently developed systems have advanced the state of the art with respect to accuracy, ability to scale to thousands of proteins and flexibility in comparing proteins that do not share the same domain architecture. New multiple alignment benchmark databases include PREFAB, SABMARK, OXBENCH and IRMBASE. Although CLUSTALW is still the most popular alignment tool to date, recent methods offer significantly better alignment quality and, in some cases, reduced computational cost.
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110
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Shih ACC, Lee DT, Lin L, Peng CL, Chen SH, Wu YW, Wong CY, Chou MY, Shiao TC, Hsieh MF. SinicView: a visualization environment for comparisons of multiple nucleotide sequence alignment tools. BMC Bioinformatics 2006; 7:103. [PMID: 16509994 PMCID: PMC1434773 DOI: 10.1186/1471-2105-7-103] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2005] [Accepted: 03/02/2006] [Indexed: 01/22/2023] Open
Abstract
Background Deluged by the rate and complexity of completed genomic sequences, the need to align longer sequences becomes more urgent, and many more tools have thus been developed. In the initial stage of genomic sequence analysis, a biologist is usually faced with the questions of how to choose the best tool to align sequences of interest and how to analyze and visualize the alignment results, and then with the question of whether poorly aligned regions produced by the tool are indeed not homologous or are just results due to inappropriate alignment tools or scoring systems used. Although several systematic evaluations of multiple sequence alignment (MSA) programs have been proposed, they may not provide a standard-bearer for most biologists because those poorly aligned regions in these evaluations are never discussed. Thus, a tool that allows cross comparison of the alignment results obtained by different tools simultaneously could help a biologist evaluate their correctness and accuracy. Results In this paper, we present a versatile alignment visualization system, called SinicView, (for Sequence-aligning INnovative and Interactive Comparison VIEWer), which allows the user to efficiently compare and evaluate assorted nucleotide alignment results obtained by different tools. SinicView calculates similarity of the alignment outputs under a fixed window using the sum-of-pairs method and provides scoring profiles of each set of aligned sequences. The user can visually compare alignment results either in graphic scoring profiles or in plain text format of the aligned nucleotides along with the annotations information. We illustrate the capabilities of our visualization system by comparing alignment results obtained by MLAGAN, MAVID, and MULTIZ, respectively. Conclusion With SinicView, users can use their own data sequences to compare various alignment tools or scoring systems and select the most suitable one to perform alignment in the initial stage of sequence analysis.
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Affiliation(s)
| | - DT Lee
- Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan
- Genomics Research Center, Academia Sinica, Taipei, 115, Taiwan
| | - Laurent Lin
- Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan
| | - Chin-Lin Peng
- Genomics Research Center, Academia Sinica, Taipei, 115, Taiwan
| | - Shiang-Heng Chen
- Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan
| | - Yu-Wei Wu
- Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan
| | - Chun-Yi Wong
- Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan
| | - Meng-Yuan Chou
- Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan
| | - Tze-Chang Shiao
- Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan
| | - Mu-Fen Hsieh
- Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan
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111
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Ebert J, Brutlag D. Development and validation of a consistency based multiple structure alignment algorithm. Bioinformatics 2006; 22:1080-7. [PMID: 16473868 DOI: 10.1093/bioinformatics/btl046] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
SUMMARY We introduce an algorithm that uses the information gained from simultaneous consideration of an entire group of related proteins to create multiple structure alignments (MSTAs). Consistency-based alignment (CBA) first harnesses the information contained within regions that are consistently aligned among a set of pairwise superpositions in order to realign pairs of proteins through both global and local refinement methods. It then constructs a multiple alignment that is maximally consistent with the improved pairwise alignments. We validate CBA's alignments by assessing their accuracy in regions where at least two of the aligned structures contain the same conserved sequence motif. RESULTS CBA correctly aligns well over 90% of motif residues in superpositions of proteins belonging to the same family or superfamily, and it outperforms a number of previously reported MSTA algorithms.
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Affiliation(s)
- Jessica Ebert
- Program in Biophysics and Department of Biochemistry, Stanford University Stanford, CA 94305, USA
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112
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Do CB, Gross SS, Batzoglou S. CONTRAlign: Discriminative Training for Protein Sequence Alignment. LECTURE NOTES IN COMPUTER SCIENCE 2006. [DOI: 10.1007/11732990_15] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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113
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Rosenberg MS. Multiple sequence alignment accuracy and evolutionary distance estimation. BMC Bioinformatics 2005; 6:278. [PMID: 16305750 PMCID: PMC1318491 DOI: 10.1186/1471-2105-6-278] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2005] [Accepted: 11/23/2005] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Sequence alignment is a common tool in bioinformatics and comparative genomics. It is generally assumed that multiple sequence alignment yields better results than pair wise sequence alignment, but this assumption has rarely been tested, and never with the control provided by simulation analysis. This study used sequence simulation to examine the gain in accuracy of adding a third sequence to a pair wise alignment, particularly concentrating on how the phylogenetic position of the additional sequence relative to the first pair changes the accuracy of the initial pair's alignment as well as their estimated evolutionary distance. RESULTS The maximal gain in alignment accuracy was found not when the third sequence is directly intermediate between the initial two sequences, but rather when it perfectly subdivides the branch leading from the root of the tree to one of the original sequences (making it half as close to one sequence as the other). Evolutionary distance estimation in the multiple alignment framework, however, is largely unrelated to alignment accuracy and rather is dependent on the position of the third sequence; the closer the branch leading to the third sequence is to the root of the tree, the larger the estimated distance between the first two sequences. CONCLUSION The bias in distance estimation appears to be a direct result of the standard greedy progressive algorithm used by many multiple alignment methods. These results have implications for choosing new taxa and genomes to sequence when resources are limited.
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Affiliation(s)
- Michael S Rosenberg
- Center for Evolutionary Functional Genomics, The Biodesign Institute, and the School of Life Sciences, Arizona State University, Tempe, AZ 85287-4501, USA.
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114
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Darzentas N, Rigoutsos I, Ouzounis CA. Sensitive detection of sequence similarity using combinatorial pattern discovery: A challenging study of two distantly related protein families. Proteins 2005; 61:926-37. [PMID: 16224785 DOI: 10.1002/prot.20608] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
We investigate the performance of combinatorial pattern discovery to detect remote sequence similarities in terms of both biological accuracy and computational efficiency for a pair of distantly related families, as a case study. The two families represent the cupredoxins and multicopper oxidases, both containing blue copper-binding domains. These families present a challenging case due to low sequence similarity, different local structure, and variable sequence conservation at their copper-binding active sites. In this study, we investigate a new approach for automatically identifying weak sequence similarities that is based on combinatorial pattern discovery. We compare its performance with a traditional, HMM-based scheme and obtain estimates for sensitivity and specificity of the two approaches. Our analysis suggests that pattern discovery methods can be substantially more sensitive in detecting remote protein relationships while at the same time guaranteeing high specificity.
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Affiliation(s)
- Nikos Darzentas
- Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge, UK
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115
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Lupyan D, Leo-Macias A, Ortiz AR. A new progressive-iterative algorithm for multiple structure alignment. Bioinformatics 2005; 21:3255-63. [PMID: 15941743 DOI: 10.1093/bioinformatics/bti527] [Citation(s) in RCA: 112] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
MOTIVATION Multiple structure alignments are becoming important tools in many aspects of structural bioinformatics. The current explosion in the number of available protein structures demands multiple structural alignment algorithms with an adequate balance of accuracy and speed, for large scale applications in structural genomics, protein structure prediction and protein classification. RESULTS A new multiple structural alignment program, MAMMOTH-mult, is described. It is demonstrated that the alignments obtained with the new method are an improvement over previous manual or automatic alignments available in several widely used databases at all structural levels. Detailed analysis of the structural alignments for a few representative cases indicates that MAMMOTH-mult delivers biologically meaningful trees and conservation at the sequence and structural levels of functional motifs in the alignments. An important improvement over previous methods is the reduction in computational cost. Typical alignments take only a median time of 5 CPU seconds in a single R12000 processor. MAMMOTH-mult is particularly useful for large scale applications. AVAILABILITY http://ub.cbm.uam.es/mammoth/mult.
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Affiliation(s)
- Dmitry Lupyan
- Department of Physiology and Biophysics, Mount Sinai School of Medicine, New York, NY 10029, USA
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116
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Abstract
S4 is an automatically generated database of multiple structure-based sequence alignments of protein superfamilies in the SCOP database. All structural domains that do not share more than 40% sequence identity as defined by the ASTRAL compendium of protein structures are included. The alignments are constructed using pairwise structural alignments to generate residue equivalences that are then integrated into multiple alignments using sequence alignment tools. We describe the database and give examples showing how the automatically generated S4 alignments compare favourably to hand-crafted alignments. Available at: http://compbio.mds.qmw.ac.uk/S4.html.
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Affiliation(s)
- James Casbon
- Institute for Cell and Molecular Science, Bart's and The London, Queen Mary's School of Medicine and Dentistry, University of London, 32 Newark Street, London E1 2AA, UK
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117
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Subramanian AR, Weyer-Menkhoff J, Kaufmann M, Morgenstern B. DIALIGN-T: an improved algorithm for segment-based multiple sequence alignment. BMC Bioinformatics 2005; 6:66. [PMID: 15784139 PMCID: PMC1087830 DOI: 10.1186/1471-2105-6-66] [Citation(s) in RCA: 113] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2004] [Accepted: 03/22/2005] [Indexed: 11/10/2022] Open
Abstract
Background We present a complete re-implementation of the segment-based approach to multiple protein alignment that contains a number of improvements compared to the previous version 2.2 of DIALIGN. This previous version is superior to Needleman-Wunsch-based multi-alignment programs on locally related sequence sets. However, it is often outperformed by these methods on data sets with global but weak similarity at the primary-sequence level. Results In the present paper, we discuss strengths and weaknesses of DIALIGN in view of the underlying objective function. Based on these results, we propose several heuristics to improve the segment-based alignment approach. For pairwise alignment, we implemented a fragment-chaining algorithm that favours chains of low-scoring local alignments over isolated high-scoring fragments. For multiple alignment, we use an improved greedy procedure that is less sensitive to spurious local sequence similarities. To evaluate our method on globally related protein families, we used the well-known database BAliBASE. For benchmarking tests on locally related sequences, we created a new reference database called IRMBASE which consists of simulated conserved motifs implanted into non-related random sequences. Conclusion On BAliBASE, our new program performs significantly better than the previous version of DIALIGN and is comparable to the standard global aligner CLUSTAL W, though it is outperformed by some newly developed programs that focus on global alignment. On the locally related test sets in IRMBASE, our method outperforms all other programs that we evaluated.
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Affiliation(s)
- Amarendran R Subramanian
- University of Tübingen, Wilhelm-Schickard-Institut für Informatik, Sand 13, 72076 Tübingen, Germany
| | - Jan Weyer-Menkhoff
- University of Göttingen, Institute of Microbiology and Genetics, Goldschmidtstr. 1, 37077 Göttingen, Germany
| | - Michael Kaufmann
- University of Tübingen, Wilhelm-Schickard-Institut für Informatik, Sand 13, 72076 Tübingen, Germany
| | - Burkhard Morgenstern
- University of Göttingen, Institute of Microbiology and Genetics, Goldschmidtstr. 1, 37077 Göttingen, Germany
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118
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Katoh K, Kuma KI, Toh H, Miyata T. MAFFT version 5: improvement in accuracy of multiple sequence alignment. Nucleic Acids Res 2005; 33:511-8. [PMID: 15661851 PMCID: PMC548345 DOI: 10.1093/nar/gki198] [Citation(s) in RCA: 3370] [Impact Index Per Article: 177.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
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 ∼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.
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Affiliation(s)
- Kazutaka Katoh
- Bioinformatics Center, Institute for Chemical Research, Kyoto University Uji, Kyoto 611-0011, Japan.
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119
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Pettersson EU, Ljunggren EL, Morrison DA, Mattsson JG. Functional analysis and localisation of a delta-class glutathione S-transferase from Sarcoptes scabiei. Int J Parasitol 2005; 35:39-48. [PMID: 15619514 DOI: 10.1016/j.ijpara.2004.09.006] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2004] [Revised: 09/15/2004] [Accepted: 09/17/2004] [Indexed: 11/30/2022]
Abstract
The mite Sarcoptes scabiei causes sarcoptic mange, or scabies, a disease that affects both animals and humans worldwide. Our interest in S. scabiei led us to further characterise a glutathione S-transferase. This multifunctional enzyme is a target for vaccine and drug development in several parasitic diseases. The S. scabiei glutathione S-transferase open reading frame reported here is 684 nucleotides long and yields a protein with a predicted molecular mass of 26 kDa. Through phylogenetic analysis the enzyme was classified as a delta-class glutathione S-transferase, and our paper is the first to report that delta-class glutathione S-transferases occur in organisms other than insects. The recombinant S. scabiei glutathione S-transferase was expressed in Escherichia coli via three different constructs and purified for biochemical analysis. The S. scabiei glutathione S-transferase was active towards the substrate 1-chloro-2,4-dinitrobenzene, though the positioning of fusion partners influenced the kinetic activity of the enzyme. Polyclonal antibodies raised against S. scabiei glutathione S-transferase specifically localised the enzyme to the integument of the epidermis and cavities surrounding internal organs in adult parasites. However, some minor staining of parasite intestines was observed. No staining was seen in host tissues, nor could we detect any antibody response against S. scabiei glutathione S-transferase in sera from naturally S. scabiei infected dogs or pigs. Additionally, the polyclonal sera raised against recombinant S. scabiei glutathione S-transferase readily detected a protein from mites, corresponding to the predicted size of native glutathione S-transferase.
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Affiliation(s)
- Eva U Pettersson
- Department of Parasitology (SWEPAR), National Veterinary Institute and Swedish University of Agricultural Sciences, SE-751 89 Uppsala, Sweden
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120
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Van Walle I, Lasters I, Wyns L. SABmark--a benchmark for sequence alignment that covers the entire known fold space. Bioinformatics 2004; 21:1267-8. [PMID: 15333456 DOI: 10.1093/bioinformatics/bth493] [Citation(s) in RCA: 181] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The Sequence Alignment Benchmark (SABmark) provides sets of multiple alignment problems derived from the SCOP classification. These sets, Twilight Zone and Superfamilies, both cover the entire known fold space using sequences with very low to low, and low to intermediate similarity, respectively. In addition, each set has an alternate version in which unalignable but apparently similar sequences are added to each problem.
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Affiliation(s)
- Ivo Van Walle
- Department of Ultrastructure, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium.
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121
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O'Sullivan O, Suhre K, Abergel C, Higgins DG, Notredame C. 3DCoffee: Combining Protein Sequences and Structures within Multiple Sequence Alignments. J Mol Biol 2004; 340:385-95. [PMID: 15201059 DOI: 10.1016/j.jmb.2004.04.058] [Citation(s) in RCA: 238] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2003] [Revised: 04/20/2004] [Accepted: 04/22/2004] [Indexed: 02/06/2023]
Abstract
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.
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Affiliation(s)
- Orla O'Sullivan
- Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland
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