Evaluation of structural similarity based on reduced dimensionality representations of protein structure.

2.50
Hdl Handle:
http://hdl.handle.net/10547/294865
Title:
Evaluation of structural similarity based on reduced dimensionality representations of protein structure.
Authors:
Albrecht, Birgit; Grant, Guy H.; Richards, W. Graham
Abstract:
Protein similarity estimations can be achieved using reduced dimensional representations and we describe a new application for the generation of two-dimensional maps from the three-dimensional structure. The code for the dimensionality reduction is based on the concept of pseudo-random generation of two-dimensional coordinates and Monte Carlo-like acceptance criteria for the generated coordinates. A new method for calculating protein similarity is developed by introducing a distance-dependent similarity field. Similarity of two proteins is derived from similarity field indices between amino acids based on various criteria such as hydrophobicity, residue replacement factors and conformational similarity, each showing a one factor Gaussian dependence. Results on comparisons of misfolded protein models with data sets of correctly folded structures show that discrimination between correctly folded and misfolded structures is possible. Tests were carried out on five different proteins, comparing a misfolded protein structure with members of the same topology, architecture, family and domain according to the CATH classification.
Citation:
Albrecht, B., Grant, G.H. and Richards, W.G. (2004) 'Evaluation of structural similarity based on reduced dimensionality representations of protein structure', Protein Engineering, Design and Selection, 17, pp. 425–432.
Publisher:
Oxford University Press
Journal:
Protein Engineering, Design and Selection
Issue Date:
2004
URI:
http://hdl.handle.net/10547/294865
PubMed ID:
15187225
Additional Links:
http://www.ncbi.nlm.nih.gov/pubmed/15187225
Type:
Article
Language:
en
ISSN:
1741-0126
Appears in Collections:
Cell and Cryobiology Research Group

Full metadata record

DC FieldValue Language
dc.contributor.authorAlbrecht, Birgiten_GB
dc.contributor.authorGrant, Guy H.en_GB
dc.contributor.authorRichards, W. Grahamen_GB
dc.date.accessioned2013-06-28T09:44:35Z-
dc.date.available2013-06-28T09:44:35Z-
dc.date.issued2004-
dc.identifier.citationAlbrecht, B., Grant, G.H. and Richards, W.G. (2004) 'Evaluation of structural similarity based on reduced dimensionality representations of protein structure', Protein Engineering, Design and Selection, 17, pp. 425–432.en_GB
dc.identifier.issn1741-0126-
dc.identifier.pmid15187225-
dc.identifier.urihttp://hdl.handle.net/10547/294865-
dc.description.abstractProtein similarity estimations can be achieved using reduced dimensional representations and we describe a new application for the generation of two-dimensional maps from the three-dimensional structure. The code for the dimensionality reduction is based on the concept of pseudo-random generation of two-dimensional coordinates and Monte Carlo-like acceptance criteria for the generated coordinates. A new method for calculating protein similarity is developed by introducing a distance-dependent similarity field. Similarity of two proteins is derived from similarity field indices between amino acids based on various criteria such as hydrophobicity, residue replacement factors and conformational similarity, each showing a one factor Gaussian dependence. Results on comparisons of misfolded protein models with data sets of correctly folded structures show that discrimination between correctly folded and misfolded structures is possible. Tests were carried out on five different proteins, comparing a misfolded protein structure with members of the same topology, architecture, family and domain according to the CATH classification.en_GB
dc.language.isoenen
dc.publisherOxford University Pressen_GB
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pubmed/15187225en_GB
dc.titleEvaluation of structural similarity based on reduced dimensionality representations of protein structure.en
dc.typeArticleen
dc.identifier.journalProtein Engineering, Design and Selectionen_GB

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