Bjoern Kolbeck

Publications (2)6.14 Total impact

• Article: Circular permuted proteins in the universe of protein folds.

  Tobias Schmidt-Goenner, Aysam Guerler, Bjoern Kolbeck, Ernst Walter Knapp
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  ABSTRACT: Finding and identifying circular permuted protein pairs (CPP) is one of the harder tasks for structure alignment programs, because of the different location of the break in the polypeptide chain connectivity. The protein structure alignment tool GANGSTA+ was used to search for CPPs in a database of nearly 10,000 protein structures. It also allows determination of the statistical significance of the occurrence of circular permutations in the protein universe. The number of detected CPPs was found to be higher than expected, raising questions about the evolutionary processes leading to CPPs. The GANGSTA+ protein structure alignment tool is available online via the web server at http://gangsta.chemie.fu-berlin.de. On the same webpage the complete data base of similar protein structure pairs based on the ASTRAL40 set of protein domains is provided and one can select CPPs specifically.
  Proteins Structure Function and Bioinformatics 05/2010; 78(7):1618-30. · 3.39 Impact Factor
• Source

  Available from: Ernst-Walter Knapp

  Article: Connectivity independent protein-structure alignment: a hierarchical approach.

  Bjoern Kolbeck, Patrick May, Tobias Schmidt-Goenner, Thomas Steinke, Ernst-Walter Knapp
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  ABSTRACT: Protein-structure alignment is a fundamental tool to study protein function, evolution and model building. In the last decade several methods for structure alignment were introduced, but most of them ignore that structurally similar proteins can share the same spatial arrangement of secondary structure elements (SSE) but differ in the underlying polypeptide chain connectivity (non-sequential SSE connectivity). We perform protein-structure alignment using a two-level hierarchical approach implemented in the program GANGSTA. On the first level, pair contacts and relative orientations between SSEs (i.e. alpha-helices and beta-strands) are maximized with a genetic algorithm (GA). On the second level residue pair contacts from the best SSE alignments are optimized. We have tested the method on visually optimized structure alignments of protein pairs (pairwise mode) and for database scans. For a given protein structure, our method is able to detect significant structural similarity of functionally important folds with non-sequential SSE connectivity. The performance for structure alignments with strictly sequential SSE connectivity is comparable to that of other structure alignment methods. As demonstrated for several applications, GANGSTA finds meaningful protein-structure alignments independent of the SSE connectivity. GANGSTA is able to detect structural similarity of protein folds that are assigned to different superfamilies but nevertheless possess similar structures and perform related functions, even if these proteins differ in SSE connectivity.
  BMC Bioinformatics 02/2006; 7:510. · 2.75 Impact Factor