A closer look on protein unfolding Simulations through hierarchical clustering

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2007

Autores

Ferreira, PG (Autor) Outra; Silva, CG (Autor) Outra; Brito, RMM (Autor) Outra; Azevedo, PJ (Autor) Outra

Ata de Conferência Internacional

Título: 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology

Páginas: 461-468

IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology

Honolulu, HI, APR 01-05, 2007

Indexação

ISI Web of Knowledge - 3 Citações

Scopus - 5 Citações

Classificação Científica

CORDIS: Ciências Físicas > Ciência de computadores > Informática

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-004-F67

Abstract (EN): Understanding protein folding and unfolding mechanisms are a central problem in molecular biology. Data obtained from molecular dynamics unfolding simulations may provide valuable insights for a better understanding of these mechanisms. Here, we propose the application of an augmented version of hierarchical clustering analysis to detect clusters of amino-acid residues with similar behavior in protein unfolding simulations. These clusters hold similar global pattern behavior of solvent accessible surface area (SASA) variation in unfolding simulations of the protein Transthyretin (TTR). Classical hierarchical clustering was applied to build a dendrogram based on the SASA variation of each amino-acid residue. The dendrogram was enriched with background information on the amino-acid residues, enabling the extraction of sub-clusters with well differentiated characteristics.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8