Sequence alignments classes

For each fold one searches for the best alignment of the target sequence that would be compatible with the fold the core should comprise hydrophobic residues and polar residues should be on the outside, predicted helical and strand regions should be aligned to corresponding secondary structure elements in the fold, and so on. In order to match a sequence alignment to a fold, Eisenberg developed a rapid method called the 3D profile method. The environment of each residue position in the known 3D structure is characterized on the basis of three properties (1) the area of the side chain that is buried by other protein atoms, (2) the fraction of side chain area that is covered by polar atoms, and (3) the secondary stmcture, which is classified in three states helix, sheet, and coil. The residue positions are rather arbitrarily divided into six classes by properties 1 and 2, which in combination with property 3 yields 18 environmental classes. This classification of environments enables a protein structure to be coded by a sequence in an 18-letter alphabet, in which each letter represents the environmental class of a residue position. 

Figure 6 Sequence alignment of lantibiotic and nonlantibiotic bacteriocin prepeptides. The residues in red indicate those positions that are fully conserved within that class, and those in blue are highly conserved. For the nonlantibiotic bacteriocins, only the leader sequences are shown. The site of proteolysis is indicated by the arrow. For cytolysin, the additional six residues removed by CylA are indicated in green.

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). ... 

On the basis of sequence alignment, subtilisin-type proteases can be subdivided into class I and class II.42 Subtilisins, thermitase and others, none of which has a disulfide bond, belong to class I, and ten proteases including aqualysin I and proteinase K to class II. An alkaline protease from Aspergillus oryzae, which has no cysteine residue, belongs to class II. The sequence identity between aqualysin I and the alkaline protease is 44%.49 ... 

The superfamily of plant, fungal, and bacterial heme peroxidases (also called non animal peroxidase superfamily, see Chap. 2) categorizes its components into three classes based on sequence alignment and biological origin, such as initially proposed by K.G. Welinder using the only crystal structure available at that moment (yeast CCP) as a model [3, 4]. Class III is the largest one, with over 3,000 plant peroxidase entries in PeroxiBase, followed by Classes I and II, with over 900 entries... 

Initial evidence for the structural diversification of the /fa-barrel fold by circular permutation was found in sequence alignments of members of the a-amylase superfamily [31]. More recently, analysis of crystallographic data of transaldolase B from E. coli suggested that the enzyme was derived from circular permutation of a class I aldolase [32]. In either case, the shift of the two N-terminal /fa-repeats (plus the /(-strand of the third subunit for amylases) onto the C-terminus resulted in no apparent functional changes. 

Fig. 5. Platform sequence alignments of the MHC class I-like ligands of NKG2D. Sequences of MIC-A and -B, the ULBPs and the RAE-ls have been aligned, divided by family and domain, using CLUSTALW (Thompson et al, 1994). Note that the alignments across families are only very approximate at these levels of sequence identity. Sequences have been numbered from the initiator methionine in the leader peptide, but only the residues in the mature proteins have been shown. Cysteines have been highlighted, and disulhde bond partners have been indicated with matching symbols (, f). For the MIC sequences, allelic substitutions have been indicated by the additional residues shown below the sequences (deletions are indicated with an X ). Diamonds below the sequences indicate NKC2D contact positions, based on the known complex structures (MIC-A 001, ULBPS, and RAE-1/5).

Table 1. Sequence alignment between the transmembrane helices of bR (Helix 1 -Helix 7) and those reported in various GPCR models based on the bR template . The P2-AR sequence is recorded here for reference even when the authors have modelled other receptors. In each helix, residues in bold are class A sequence motifs or residues involved in ligand binding. A shift if 3 or 4 residues corresponds to a difference of 1 turn and a vertical displacement of about 5 A.

Figure 2. Comparison of sequence variability among functional TEM-1 p-lactamase mutants and twenty aligned class A P-lactamases. The wild type TEM-1 -lactamase primary sequence is shown. Above the sequence are the different amino acids that were identified at that sequence position among functional random mutants. Below the TEM-1 primary sequence are the different amino acids that appear at these positions in an alignment of 20 class A P-lactamases (Figure adapted from Huang et al., 1996).

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