Difference between revisions of "Multiple sequence alignment"
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Revision as of 23:05, 18 November 2013
Multiple sequence alignment
Summary ...
Contents
Further reading and resources
- Sequence alignment
- Multiple sequence alignment
- List of alignment visualization software
- Sequence alignment software (Very comprehensive list!)
Benítez-Páez et al. (2012) A practical guide for the computational selection of residues to be experimentally characterized in protein families. Brief Bioinformatics 13:329-36. (pmid: 21930656) |
[ PubMed ] [ DOI ] In recent years, numerous biocomputational tools have been designed to extract functional and evolutionary information from multiple sequence alignments (MSAs) of proteins and genes. Most biologists working actively on the characterization of proteins from a single or family perspective use the MSA analysis to retrieve valuable information about amino acid conservation and the functional role of residues in query protein(s). In MSAs, adjustment of alignment parameters is a key point to improve the quality of MSA output. However, this issue is frequently underestimated and/or misunderstood by scientists and there is no in-depth knowledge available in this field. This brief review focuses on biocomputational approaches complementary to MSA to help distinguish functional residues in protein families. These additional analyses involve issues ranging from phylogenetic to statistical, which address the detection of amino acids pivotal for protein function at any level. In recent years, a large number of tools has been designed for this very purpose. Using some of these relevant, useful tools, we have designed a practical pipeline to perform in silico studies with a view to improving the characterization of family proteins and their functional residues. This review-guide aims to present biologists a set of specially designed tools to study proteins. These tools are user-friendly as they use web servers or easy-to-handle applications. Such criteria are essential for this review as most of the biologists (experimentalists) working in this field are unfamiliar with these biocomputational analysis approaches. |
Kemena & Notredame (2009) Upcoming challenges for multiple sequence alignment methods in the high-throughput era. Bioinformatics 25:2455-65. (pmid: 19648142) |
[ PubMed ] [ DOI ] This review focuses on recent trends in multiple sequence alignment tools. It describes the latest algorithmic improvements including the extension of consistency-based methods to the problem of template-based multiple sequence alignments. Some results are presented suggesting that template-based methods are significantly more accurate than simpler alternative methods. The validation of existing methods is also discussed at length with the detailed description of recent results and some suggestions for future validation strategies. The last part of the review addresses future challenges for multiple sequence alignment methods in the genomic era, most notably the need to cope with very large sequences, the need to integrate large amounts of experimental data, the need to accurately align non-coding and non-transcribed sequences and finally, the need to integrate many alternative methods and approaches. |
Waterhouse et al. (2009) Jalview Version 2--a multiple sequence alignment editor and analysis workbench. Bioinformatics 25:1189-91. (pmid: 19151095) |
[ PubMed ] [ DOI ] UNLABELLED: Jalview Version 2 is a system for interactive WYSIWYG editing, analysis and annotation of multiple sequence alignments. Core features include keyboard and mouse-based editing, multiple views and alignment overviews, and linked structure display with Jmol. Jalview 2 is available in two forms: a lightweight Java applet for use in web applications, and a powerful desktop application that employs web services for sequence alignment, secondary structure prediction and the retrieval of alignments, sequences, annotation and structures from public databases and any DAS 1.53 compliant sequence or annotation server. AVAILABILITY: The Jalview 2 Desktop application and JalviewLite applet are made freely available under the GPL, and can be downloaded from www.jalview.org. |
Pei & Grishin (2001) AL2CO: calculation of positional conservation in a protein sequence alignment. Bioinformatics 17:700-12. (pmid: 11524371) |
[ PubMed ] [ DOI ] 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/. |