Systematic comparison of SCOP and CATH: a new gold standard for protein structure analysis

Csaba, Gergely; Birzele, Fabian und Zimmer, Ralf (2009): Systematic comparison of SCOP and CATH: a new gold standard for protein structure analysis. In: BMC Structural Biology 9:23

Abstract

Background: SCOP and CATH are widely used as gold standards to benchmark novel protein structure comparison methods as well as to train machine learning approaches for protein structure classification and prediction. The two hierarchies result from different protocols which may result in differing classifications of the same protein. Ignoring such differences leads to problems when being used to train or benchmark automatic structure classification methods. Here, we propose a method to compare SCOP and CATH in detail and discuss possible applications of this analysis. Results: We create a new mapping between SCOP and CATH and define a consistent benchmark set which is shown to largely reduce errors made by structure comparison methods such as TM-Align and has useful further applications, e. g. for machine learning methods being trained for protein structure classification. Additionally, we extract additional connections in the topology of the protein fold space from the orthogonal features contained in SCOP and CATH. Conclusion: Via an all-to-all comparison, we find that there are large and unexpected differences between SCOP and CATH w.r.t. their domain definitions as well as their hierarchic partitioning of the fold space on every level of the two classifications. A consistent mapping of SCOP and CATH can be exploited for automated structure comparison and classification. Availability: Benchmark sets and an interactive SCOP-CATH browser are available at http://www.bio.ifi.lmu.de/SCOPCath.

• Dokumententyp: Zeitschriftenartikel
• Publikationsform: Publisher's Version
• Fakultät: Mathematik, Informatik und Statistik > Informatik
• Themengebiete: 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften; Biologie
• ISSN: 1472-6807
• Sprache: Englisch