Towards an automatic classification of protein structural domains based on structural similarity

Background: Formal classification of a large collection of protein structures aids the understanding of evolutionary relationships among them. Classifications involving manual steps, such as SCOP and CATH, face the challenge of increasing volume of available structures. Automatic methods such as FSSP or Dali Domain Dictionary, yield divergent classifications, for reasons not yet fully investigated. One possible reason is that the pairwise similarity scores used in automatic classification do not adequately reflect the judgments made in manual classification. Another possibility is the difference between manual and automatic classification procedures. We explore the degree to which these two factors might affect the final classification. Results: We use DALI, SHEBA and VAST pairwise scores on the SCOP C class domains, to investigate a variety of hierarchical clustering procedures. The constructed dendrogram is cut in a variety of ways to produce a partition, which is compared to the SC...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Vichetra Sam, Chin-Hsien Tai, Jean Garnier, Jean-François Gibrat, Byungkook Lee, Peter J. Munson
• Keywords: Automatic Classification, BMCBI 2008, Pairwise Similarity Scores, SCOP