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PMID: 15746292 Published · ppublish English Evaluation Study Journal Article Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S. Research Support, U.S. Gov't, P.H.S.

Multiple flexible structure alignment using partial order graphs.

Bioinformatics (Oxford, England) ·Vol. 21 ·No. 10 ·2005-05-15 ·Pages 2362-9

Ye Y, Godzik A

Abstract

Existing comparisons of protein structures are not able to describe structural divergence and flexibility in the structures being compared because they focus on identifying a common invariant core and ignore parts of the structures outside this core. Understanding the structural divergence and flexibility is critical for studying the evolution of functions and specificities of proteins. A new method of multiple protein structure alignment, POSA (Partial Order Structure Alignment), was developed using a partial order graph representation of multiple alignments. POSA has two unique features: (1) identifies and classifies regions that are conserved only in a subset of input structures and (2) allows internal rearrangements in protein structures. POSA outperforms other programs in the cases where structural flexibilities exist and provides new insights by visualizing the mosaic nature of multiple structural alignments. POSA is an ideal tool for studying the variation of protein structures within diverse structural families. POSA is freely available for academic users on a Web server at http://fatcat.burnham.org/POSA

MeSH Terms
Algorithms Amino Acid Sequence Computer Simulation Evolution, Molecular Models, Chemical Models, Molecular Molecular Sequence Data Protein Conformation Proteins/analysis,chemistry,genetics Sequence Alignment/methods Sequence Analysis, Protein/methods Software Structure-Activity Relationship
Chemicals
Proteins
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Ye Yuzhen
Program in Bioinformatics and Systems Biology, The Burnham Institute, 10901 N. Torrey Pines Road, La Jolla, CA 92037, USA. [email protected]
Godzik Adam
Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4803
Published
2005-05-15
Epub
2005-00-03
Pages
2362-9
Language
English
Region
England
NLM ID
9808944
Subset
IM
Grants
NIGMS NIH HHS · GM63208 · United States
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