A dihedral angle database of short sub-sequences for protein structure prediction

Dayalan, S, Bevinakoppa, S and Schroder, H 2004, 'A dihedral angle database of short sub-sequences for protein structure prediction', in Bioinformatics 2004 - Proceedings of the Second Asia-Pacific Bioinformatics Conference, Dunedin, 18-22 January 2004.


Document type: Conference Paper
Collection: Conference Papers

Title A dihedral angle database of short sub-sequences for protein structure prediction
Author(s) Dayalan, S
Bevinakoppa, S
Schroder, H
Year 2004
Conference name Asia-Pacific Bioinformatics Conference
Conference location Dunedin
Conference dates 18-22 January 2004
Proceedings title Bioinformatics 2004 - Proceedings of the Second Asia-Pacific Bioinformatics Conference
Publisher Australian Computer Society
Place of publication Bedford Park, SA
Abstract Protein structure prediction is considered to be the holy grail of bioinformatics. Ab initio and homology modelling are two important groups of methods used in protein structure prediction. Amongst these, ab initio methods assume that no previous knowledge about protein structures is required. On the other hand homology modelling is based on sequence similarity and uses information such as classification, structure, sequence and dihedral angles for prediction.Even though there are many databases for structural and sequence information, there are not many databases for dihedral angles that store all occurring dihedral values of sub-sequences. The existing ones have limitations like not being able to retrieve dihedral values for amino acids of a specific sub-sequence or being designed only for a specific set of proteins based on sequence identity (proteins with < 20% sequence identity). They hence have disadvantages when used in protein structure prediction based on short sub-sequences and exact matches. This paper presents a dihedral angle database for short sub-sequences up to length five. In this database dihedral angles of all proteins were extracted from the Protein Data Bank (PDB) regardless of the percent of sequence similarity. This paper also shows how the database can be used for protein structure prediction using exact matches.
Subjects Information Systems not elsewhere classified
Keyword(s) dihedral angle
homology modelling
protein structure prediction
sub-sequence
Copyright notice Copyright © 2004, Australian Computer Society, Inc.
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