title: The recognition of protein structure and function from sequence: adding value to genome data.
abstract: The explosion of DNA sequence data from genome projects presents many challenges. For instance, we must extend our current knowledge of protein structure and function so that it can be applied to these new sequences. The derivation of rules for the relationships between sequence and structure allow us to recognize a common fold by the use of tertiary templates. New techniques enable us to begin to meet the challenge of rule-based modelling of distantly related proteins. This paper describes an integrated and knowledge-based approach to the prediction of protein structure and function which can maximize the value of sequence information.
authors: Department of Crystallography, Birkbeck College, University of London, U.K.
authors: A C
authors: AC
authors: May
authors: M S
authors: MS
authors: Johnson
authors: S D
authors: SD
authors: Rufino
authors: H
authors: H
authors: Wako
authors: Z Y
authors: ZY
authors: Zhu
authors: R
authors: R
authors: Sowdhamini
authors: N
authors: N
authors: Srinivasan
authors: M A
authors: MA
authors: Rodionov
authors: T L
authors: TL
authors: Blundell
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D016282:Aspartic Acid Endopeptidases / Q000737:chemistry; D004247:DNA / Q000737:chemistry* / Q000235:genetics; D005796:Genes; D016678:Genome; D008322:Mammals; D008958:Models, Molecular; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry* / Q000235:genetics; D013329:Structure-Activity Relationship
chemical_list: D011506:Proteins; D004247:DNA; D016282:Aspartic Acid Endopeptidases