Protein sequences sequence patterns

The Sequence Retrieval System (Etzold et ah, 1996) is a network browser for databases at EBI. The system allows users to retrieve, link, and access entries from all the interconnected resources such as nucleic acid, EST, protein sequence, protein pattern, protein structure, specialist/boutique, and/or bibliographic databases. The SRS is also a database browser of DDBJ, ExPASy, and a number of servers as the query system. The SRS can be accessed from EBI Tools server at http // www2.ebi.ac.uk/Tools/index.html or directly at http //srs6.ebi.ac.uk/. The SRS permits users to formulate queries across a range of different database types via a single interface in three different methods (Figure 3.4) ... 

Key Words Sequence alignment propensity protein structures sequence pattern secondary structure. 

TL Bailey, M Grihskov. The megaprior heuristic for discovering protein sequence patterns. Intelligent Systems in Molecular Biology 4 15-24, 1996. 

The basic structural unit of these two-sheet p helix structures contains 18 amino acids, three in each p strand and six in each loop. A specific amino acid sequence pattern identifies this unit namely a double repeat of a nine-residue consensus sequence Gly-Gly-X-Gly-X-Asp-X-U-X where X is any amino acid and U is large, hydrophobic and frequently leucine. The first six residues form the loop and the last three form a p strand with the side chain of U involved in the hydrophobic packing of the two p sheets. The loops are stabilized by calcium ions which bind to the Asp residue (Figure S.28). This sequence pattern can be used to search for possible two-sheet p structures in databases of amino acid sequences of proteins of unknown structure. 

The world of zinc-containing DNA-binding proteins is by no means exhausted by these three subfamilies. Several other subfamilies are already known with different three-dimensional structures and different sequence patterns of cysteine and histidine residues that form the zinc ligands. Further subfamilies may well be discovered as the genomes of different species are sequenced whether or not any fundamentally new principles for DNA-protein recognition will be discovered amongst these new subfamilies remains to be seen. 

Gram-negative bacteria are surrounded by two membranes, an inner plasma membrane and an outer membrane. These are separated by a periplasmic space. Most plasma membrane proteins contain long, continuous sequences of about 20 hydrophobic residues that are typical of transmembrane a helices such as those found in bacteriorhodopsin. In contrast, most outer membrane proteins do not show such sequence patterns. 

The aim of the fust dimension breadth is to reveal sequence-function relationships by comparing protein sequences by sequence similarity. Simple bioinformatic algorithms can be used to compare a pair of related proteins or for sequence similarity searches e.g., BLAST (Basic Local Alignment Search Tool). Improved algorithms allow multiple alignments of larger number of proteins and extraction of consensus sequence pattern and sequence profiles or structural templates, which can be related to some functions, see e.g., under http //www. expasy.ch/tools/ similarity. 

Recently, peptoid-based mimics of both SP-C and SP-B have been designed to adopt helical secondary structures, and also mimic (to varying degrees) the sequence patterning of hydrophobic and polar residues found in the natural surfactant proteins. Peptoid-based SP-C mimics of up to 22 monomers in length, were synthesized and characterized by in vitro experimental methods [67, 68] (Fig. 1.8). The secondary structure of all molecules was assessed by circular dichroism and found to be helical. The surface activities of these peptoids, in comparison to the actual SP peptides described above, were characterized by surfactometry using... 

This procedure led to a substitution matrix for aligning disordered protein that was different from the commonly used substitution matrices, such as BLOSUM62 (Fig. 4). The matrix for disordered protein is generally better than order-based matrices for aligning disordered proteins whose sequence identities are between 20 and 50%. These results indicate that disordered and ordered protein can be distinguished by their patterns of evolutionary change. 

The delivery of male courtship pheromones is widespread among plethodontid salamanders (Houck and Arnold 2003), and other courtship pheromones are being discovered for this group (Houck, Palmer, Watts, Arnold, Feldhoff and Feldhoff 2007). The mode by which these pheromones are transferred to the female apparently has been modified from delivery via diffusion into the circulatory system to delivery that directly stimulates vomeronasal receptors (Fig. 20.1 Houck and Sever 1994 Watts et al. 2004 Palmer et al. 2005 Palmer et al. 2007). The behavior patterns and morphologies associated with these two delivery modes often remain static for millions of years. In contrast, evolution at the level of pheromone signals is apparently an incessant process that continuously alters the protein sequence and composition of pheromones both within and among species (Watts et al. 2004 Palmer et al. 2005 Palmer et al. 2007). 

Taylor, W. R. (1992) Patterns in Protein Sequence and Structure, Springer Series in Biophysics (Springer, Berlin), Vol. 7. 

Another computational approach for detecting /1-solenoid sequences is implemented in a program called BETAWRAP (Bradley et al., 2001). This approach aims to identify /1-solenoid sequences by using hydrophobic-residue sequence patterns of strand-turn-strand regions that were learned from non-/l-solenoid structures. This method also takes into consideration the repetitive character of these patterns in /1-solenoids. Unlike the sequence profile approaches, BETAWRAP can make ab initio predictions of /1-solenoid domains. However, it is less sensitive than the profile search and, sometimes, cannot distinguish /1-solenoids from other solenoids (A. V. K, unpublished observation) such as, for example, LRR proteins (Kobe and Deisenhofer, 1994 Kobe and Kajava, 2001). The latest modification of BETAWRAP algorithm, which is called BETAWRAPPRO (McDonnell et al., 2006), employs additional data provided by sequence profiles and this improves the results of /1-solenoid predictions. 

Bailey, T. L., and Gribskov, M. (1996). The megaprior heuristic for discovering protein sequence patterns. In Proceedings of the Fourth International Conference on Intelligent Systems for Molecular Biology, pp. 15-24. AAAI Press, Menlo Park. 

Was a common principle found in protein sorting Schatz and Dob-berstein (1996) discussed some similarity in import/export systems between various organelles. It is most interesting to know why apparently vague sequence patterns can be so specific. One key seems to lie in the fact that we have seen several different phenomena as a whole (as in the case of signal peptides). The next 10 years will also be exciting for sequence analysts. 

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