Local sequence alignment

Liu, J., Neuwald, A., and Lawrence, C. (1995) Bayesian models for multiple local sequence alignment and Gibbs sampling strategies. J. Amer. Stat. Assoc. 90, 1156-1170. 

The location of the indel around position 254 would be haid to find based on sequence information alone. Visual inspection of the structure around this position made clear, however, that the threonine at position 254 is sitting in a beta-bulge. This residue can be deleted with only minimal disturbance of the local environment in the structure. Additional facts in favor of this solution for the local sequence-alignment problem are that the glycine at position 256 ends up favorably in a (3-tum and that all residues seem to fit well in their three-dimensional environment. 

Fig. 10.17 Finding the irptimal local sequence alignment using the Smith-Waterman algorithm with a scoring scheme in which a match scores 1, a mismatch scores -1 and the gap penalty is —2. The algorithm identifies the conserved RCK motif.

In general, alignment-based measures can be divided into two categories global sequence alignment and local sequence alignment. 

Misleading Local Sequence Alignments Implications for Comparative Protein Modeling. 

A sequence alignment is a way of determining the similarity between two strings. This is a classical question in computer science, and has an exact solution referred to as the Smith/Waterman alignment. Unfortunately, this exact solution can be slow when analyzing large sequences, and therefore, approximate methods, such as Basic Local Alignment Search Tool (BLAST), have been developed to identify very similar sequences. 

Proteomics is concerned with the analysis of the complete protein complements of genomes. Thus proteomics includes not only the identification and quantification of proteins, but also the determination of their localization, modifications, interactions, activities, and functions. This chapter focuses on protein sequences as the sources of biochemical information. Protein sequence databases are surveyed. Similarity search and sequence alignments using the Internet resources are described. 

There are different classes of protein sequence databases. Primary and secondary databases are used to address different aspects of sequence analysis. Composite databases amalgamate a variety of different primary sources to facilitate sequence searching efficiently. The primary structure (amino acid sequence) of a protein is stored in primary databases as linear alphabets that represent the constituent residues. The secondary structure of a protein corresponding to region of local regularity (e.g., a-helices, /1-strands, and turns), which in sequence alignments are often apparent as conserved motifs, is stored in secondary databases as patterns. The tertiary structure of a protein derived from the packing of its secondary structural elements which may form folds and domains is stored in structure databases as sets of atomic coordinates. Some of the most important protein sequence databases are PIR (Protein Information Resource), SWISS-PROT (at EBI and ExPASy), MIPS (Munich Information Center for Protein Sequences), JIPID (Japanese International Protein Sequence Database), and TrEMBL (at EBI). ... 

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. 

Figure 11,4. ExPASy Proteomic tools. ExPASy server provides various tools for proteomic analysis which can be accessed from ExPASy Proteomic tools. These tools (locals or hyperlinks) include Protein identification and characterization, Translation from DNA sequences to protein sequences. Similarity searches, Pattern and profile searches, Post-translational modification prediction, Primary structure analysis, Secondary structure prediction, Tertiary structure inference, Transmembrane region detection, and Sequence alignment.

Each amino acid has distinct attributes such as size, hydrophobicity/hy-drophilicity, hydrogen bonding capacity, and conformational preferences that allow it to contribute to a protein fold. Attempts are being made to interpret the protein fold in terms of amino acid descriptors. Structural alignments are more accurate than sequence alignments, and the local physicochemical environment of every residue within each 3D structure is directly obtainable (e.g., AAindex at http //www. 

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