Linked Life Data

12833538

Source:http://linkedlifedata.com/resource/pubmed/id/12833538

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2003-6-30
pubmed:abstractText
An innovative bioinformatic method has been designed and implemented to detect similar three-dimensional (3D) sites in proteins. This approach allows the comparison of protein structures or substructures and detects local spatial similarities: this method is completely independent from the amino acid sequence and from the backbone structure. In contrast to already existing tools, the basis for this method is a representation of the protein structure by a set of stereochemical groups that are defined independently from the notion of amino acid. An efficient heuristic for finding similarities that uses graphs of triangles of chemical groups to represent the protein structures has been developed. The implementation of this heuristic constitutes a software named SuMo (Surfing the Molecules), which allows the dynamic definition of chemical groups, the selection of sites in the proteins, and the management and screening of databases. To show the relevance of this approach, we focused on two extreme examples illustrating convergent and divergent evolution. In two unrelated serine proteases, SuMo detects one common site, which corresponds to the catalytic triad. In the legume lectins family composed of >100 structures that share similar sequences and folds but may have lost their ability to bind a carbohydrate molecule, SuMo discriminates between functional and non-functional lectins with a selectivity of 96%. The time needed for searching a given site in a protein structure is typically 0.1 s on a PIII 800MHz/Linux computer; thus, in further studies, SuMo will be used to screen the PDB.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
1097-0134
pubmed:author
pubmed:copyrightInfo
Copyright 2003 Wiley-Liss, Inc.
pubmed:issnType
Electronic
pubmed:day
1
pubmed:volume
52
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
137-45
pubmed:dateRevised
2009-1-8
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
A new bioinformatic approach to detect common 3D sites in protein structures.
pubmed:affiliation
Institut de Biologie et Chimie des Protéines (IBCP), Lyon, France.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't, Evaluation Studies