Linked Life Data

12647403

Source:http://linkedlifedata.com/resource/pubmed/id/12647403

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2003-3-21
pubmed:abstractText
We are still missing a basic understanding of sequence/structure/function relationships in proteins. Analogy-based prediction algorithms remain the only reliable fold prediction tools. New methods, such as threading and hybrid threading/sequence fold recognition, can often recognize even the most distant homologues and, in some cases, even unrelated proteins with similar overall structures. This knowledge pushed the envelope of analogy-based function analysis to the point that the majority of newly sequenced genomes can be tentatively assigned to already characterized protein superfamilies. However, at this evolutionary distance, fold prediction is no longer equivalent to function prediction. Instead of having the same exact function, distantly related proteins might share some functional analogy that is not obvious to the casual observer. The main challenge facing the fold recognition field is to develop tools to follow the structure prediction with function prediction and analysis.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0076-6941
pubmed:author
pubmed:issnType
Print
pubmed:volume
44
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
525-46
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Fold recognition methods.
pubmed:affiliation
Program in Bioinformatics and Biological Diversity, Burnham Institute, La Jolla, CA, USA.
pubmed:publicationType
Journal Article, Comparative Study, Review