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Protein structure prediction from sequence variation.
Marks, Debora S; Hopf, Thomas A; Sander, Chris.
Afiliação
  • Marks DS; Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA. ecreview@hms.harvard.edu
Nat Biotechnol ; 30(11): 1072-80, 2012 Nov.
Article em En | MEDLINE | ID: mdl-23138306
ABSTRACT
Genomic sequences contain rich evolutionary information about functional constraints on macromolecules such as proteins. This information can be efficiently mined to detect evolutionary couplings between residues in proteins and address the long-standing challenge to compute protein three-dimensional structures from amino acid sequences. Substantial progress has recently been made on this problem owing to the explosive growth in available sequences and the application of global statistical methods. In addition to three-dimensional structure, the improved understanding of covariation may help identify functional residues involved in ligand binding, protein-complex formation and conformational changes. We expect computation of covariation patterns to complement experimental structural biology in elucidating the full spectrum of protein structures, their functional interactions and evolutionary dynamics.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Variação Genética / Proteínas / Modelos Moleculares / Análise de Sequência de Proteína / Modelos Químicos / Modelos Genéticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2012 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Variação Genética / Proteínas / Modelos Moleculares / Análise de Sequência de Proteína / Modelos Químicos / Modelos Genéticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2012 Tipo de documento: Article