Profiles sequence similarity search

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. 

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.

MotifSearch uses a set of profiles (representing similarities within a family of sequences) to search a sequence database. 

R. Lflthy, A. D. McLachlan, and D. Eisenbeig. Secondary structure breed profiles use protein sequence database for structural similarities. Proteins 70 229-239 (1991). 

Click on the link indicated by H next to the Nucleotide-nucleotide BLAST (blastn) to access the problem. This problem describes how to obtain single-nucleotide polymorphism (SNP) information in similar sequences in the database. Hermankova et al. (8) studied the HIV-1 drug resistance profiles in children and adults receiving combination drug therapy. To identify the SNPs in the HIV-1 isolates from these patients, or other similar sequences in the database, use the sequence from one of the patients given next and run a nucleotide-nucleotide BLAST search as described in the problem previously listed. Format the results using the Flat Query with Identities option from the Alignment View pull down menu under the Format options (see Note 3). 

PSI-BLAST [61,62] iteratively constructs a sequence profile from the highest scoring hits in a series of BLAST searches the progressively refined profile captures a sequence pattern that can potentially enhance the sensitivity of BLAST similarity... 

This may be trivial if sequence identity between the target sequence and a known 3D stmcture is high (say > 30%), as then simple pair-wise sequence comparison methods (FASTA, SSEARCH ) will easily identify the relation-ship. Where sequence identity is lower and a superfamily or even fold relationship must be identified, recognition of the stmctural similarity between two sequences may be very difficult. Sequence-only methods, such as PSI-BLAST, hidden Markov models and intermediate sequence search, use information from multiple sequence alignments to represent the characteristics shared by related sequences (sequence profiles), and use this to search for stmctural homologues. These profiles can then be augmented by secondary stmcture prediction. ... 

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