Literature DB >> 26810894

BLAST-based structural annotation of protein residues using Protein Data Bank.

Harinder Singh1, Gajendra P S Raghava2.   

Abstract

BACKGROUND: In the era of next-generation sequencing where thousands of genomes have been already sequenced; size of protein databases is growing with exponential rate. Structural annotation of these proteins is one of the biggest challenges for the computational biologist. Although, it is easy to perform BLAST search against Protein Data Bank (PDB) but it is difficult for a biologist to annotate protein residues from BLAST search.
RESULTS: A web-server StarPDB has been developed for structural annotation of a protein based on its similarity with known protein structures. It uses standard BLAST software for performing similarity search of a query protein against protein structures in PDB. This server integrates wide range modules for assigning different types of annotation that includes, Secondary-structure, Accessible surface area, Tight-turns, DNA-RNA and Ligand modules. Secondary structure module allows users to predict regular secondary structure states to each residue in a protein. Accessible surface area predict the exposed or buried residues in a protein. Tight-turns module is designed to predict tight turns like beta-turns in a protein. DNA-RNA module developed for predicting DNA and RNA interacting residues in a protein. Similarly, Ligand module of server allows one to predicted ligands, metal and nucleotides ligand interacting residues in a protein.
CONCLUSIONS: In summary, this manuscript presents a web server for comprehensive annotation of a protein based on similarity search. It integrates number of visualization tools that facilitate users to understand structure and function of protein residues. This web server is available freely for scientific community from URL http://crdd.osdd.net/raghava/starpdb .

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Year:  2016        PMID: 26810894      PMCID: PMC4727276          DOI: 10.1186/s13062-016-0106-9

Source DB:  PubMed          Journal:  Biol Direct        ISSN: 1745-6150            Impact factor:   4.540


  25 in total

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Review 4.  Integrating biological data through the genome.

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Authors:  Mark N Wass; Michael J E Sternberg
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9.  The Pfam protein families database.

Authors:  Robert D Finn; John Tate; Jaina Mistry; Penny C Coggill; Stephen John Sammut; Hans-Rudolf Hotz; Goran Ceric; Kristoffer Forslund; Sean R Eddy; Erik L L Sonnhammer; Alex Bateman
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10.  Integrating sequence and structural biology with DAS.

Authors:  Andreas Prlić; Thomas A Down; Eugene Kulesha; Robert D Finn; Andreas Kähäri; Tim J P Hubbard
Journal:  BMC Bioinformatics       Date:  2007-09-12       Impact factor: 3.169

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