A closer look on protein unfolding Simulations through hierarchical clustering

• Type: Article in International Conference Proceedings Book
• Date: 2007

Authors

Ferreira, PG (Author) Other; Silva, CG (Author) Other; Brito, RMM (Author) Other; Azevedo, PJ (Author) Other

Conference proceedings International

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

Pages: 461-468

IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology

Honolulu, HI, APR 01-05, 2007

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 5 Citations

Scientific classification

CORDIS: Physical sciences > Computer science > Informatics

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8