Sequence alignment methods

AD Baxevams. Pi actical aspects of multiple sequence alignment. Methods Biochem Anal 39 172-188, 1998. 

Edgar, R. C. 2004. MUSCLE A multiple sequence alignment method with reduced time and space complexity. BMC Bioinform 5 113. 

Waterman, M. S. Jones, R. (1990). Consensus methods for DNA and protein sequence alignment. Methods Enzymol 183,221-37. 

This chapter presents a brief summary of the essentials of statistics that are particularly appropriate for handling biochemical data. This is followed by a section on the quantitative analysis of experimental results which deals chiefly with binding processes and enzyme kinetics. The chapter concludes with a brief discussion of methods of sequence analysis and databases, including a description of the FASTA and Needleman and Wunsch algorithms which form the basis of most of the sequence alignment methods currently in use. 

Sequence-comparison methods Section 7.2 Sequence-alignment methods Sechon 7.2... 

When the sequence of a protein is first determined, comparing it with all previously characterized sequences can be a source of tremendous insight into its evolutionary relatives and, hence, its structure and function. Indeed, an extensive sequence comparison is almost always the first analysis performed on a newly elucidated sequence. The sequence alignment methods heretofore described are used to compare an individual sequence with all members of a database of known sequences. 

Higgins DG, Thompson JD, Gibson TJ (1996) Using CLUSTAL for multiple sequence alignments. Method Enzymol 266 383 102... 

Deciding how much of the template structure to remove before loop building depends on examination of the sequence alignment and the template structure. Sequence alignments with insertions and deletions are usually not unambiguous. Most sequence alignment methods ignorant of... 

Hubbard, T. J., et al., SCOP, Structural Classification of Proteins database applications to evaluation of the effectiveness of sequence alignment methods and statistics of protein structural data. Acta Crystallogr D Biol Crystallogr, 1998. 54(1 (Pt 6)) p. 1147-54. 

Multiple Sequence Alignment Methods Multiple Sequence Alignment Programs... 

The basic procedure for building a 3D protein model is to identify as many homologous sequences as possible in proteins whose 3D structure is known. Various sequence alignment methods are available. - These programs often have adjustable parameters and will generate a number of different alignments. One must be selected to be the basis for constructing the 3D model. 

Fig. 3.9. Three-dimensional G protein-coupled CB2 receptor structure (right) constructed by homology and multiple sequence alignment method (left), including the seven transmembrane helices (cylinders, l-VII) and loop regions (ribbons) (See color plate.) (From Xie XQ, Chen JZ, Billings EM. 3D structural model of the G protein-coupled...

Most sequence alignment methods seek to optimize the criterion of similarity. There are two approaches of sequence alignments a global alignment compares similarity across the full stretch of sequences while a local alignment searches for regions of similarity in parts of the sequences. 

Despite the success of sequence alignment methods in recognizing similar proteins when sequence identity is above 25 to 30%, there are many sequences with similar folds that have much lower sequence identity (7). In particular, it is difficult to distinguish structurally homologous sequences from unrelated sequences when the sequence identity is in the twilight zone region below 20-25% sequence identity (2). 

Detecting repetition by sequence alignment methods is relatively easy. However, TE identification problem is notoriously difficult because the processes of TE evolution remain questionable. The moving ability, coding capacity, duplicating process, and mutation dynamics of TEs are not well imderstood and are still debated. The integration of diverse computational tools and techniques for a comprehensive analysis of TEs is still an open challenge in Bioinformatics. 

Most sequence alignment methods are automated, but some are performed manually. Both the automated and the manual alignment of multiple chains is a challenging problem because of the myriad of alignment possibilities. The number of combinations for alignment is determined by raising the number of sequences by the number of amino acid residues of the longest sequence (Equation [1]). 

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