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Title: Protein Classification Based on Analysis of Local Sequence-Structure Correspondence

Abstract

The goal of this project was to develop an algorithm to detect and calculate common structural motifs in compared structures, and define a set of numerical criteria to be used for fully automated motif based protein structure classification. The Protein Data Bank (PDB) contains more than 33,000 experimentally solved protein structures, and the Structural Classification of Proteins (SCOP) database, a manual classification of these structures, cannot keep pace with the rapid growth of the PDB. In our approach called STRALCP (STRucture Alignment based Clustering of Proteins), we generate detailed information about global and local similarities between given set of structures, identify similar fragments that are conserved within analyzed proteins, and use these conserved regions (detected structural motifs) to classify proteins.

Authors:
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
893991
Report Number(s):
UCRL-TR-218946
TRN: US200701%%92
DOE Contract Number:
W-7405-ENG-48
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ALGORITHMS; ALIGNMENT; CLASSIFICATION; PROTEIN STRUCTURE; PROTEINS

Citation Formats

Zemla, A T. Protein Classification Based on Analysis of Local Sequence-Structure Correspondence. United States: N. p., 2006. Web. doi:10.2172/893991.
Zemla, A T. Protein Classification Based on Analysis of Local Sequence-Structure Correspondence. United States. doi:10.2172/893991.
Zemla, A T. Mon . "Protein Classification Based on Analysis of Local Sequence-Structure Correspondence". United States. doi:10.2172/893991. https://www.osti.gov/servlets/purl/893991.
@article{osti_893991,
title = {Protein Classification Based on Analysis of Local Sequence-Structure Correspondence},
author = {Zemla, A T},
abstractNote = {The goal of this project was to develop an algorithm to detect and calculate common structural motifs in compared structures, and define a set of numerical criteria to be used for fully automated motif based protein structure classification. The Protein Data Bank (PDB) contains more than 33,000 experimentally solved protein structures, and the Structural Classification of Proteins (SCOP) database, a manual classification of these structures, cannot keep pace with the rapid growth of the PDB. In our approach called STRALCP (STRucture Alignment based Clustering of Proteins), we generate detailed information about global and local similarities between given set of structures, identify similar fragments that are conserved within analyzed proteins, and use these conserved regions (detected structural motifs) to classify proteins.},
doi = {10.2172/893991},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Feb 13 00:00:00 EST 2006},
month = {Mon Feb 13 00:00:00 EST 2006}
}

Technical Report:

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