Fast Hinge Detection Algorithms for Flexible Protein Structures
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Motivation: The current DynDom database of protein domain motions is a user-created database that suffers from selectivity and redundancy. The aim of the analysis presented here was to overcome both these limitations and to produce both a comprehensive and a non-redundant description of domain movements from structures stored in the current protein data bank. Results: A multi-step procedure is applied that starts with grouping proteins in the structural databank into families based on sequence similarity. Multiple sequence alignment, conformational clustering and a dimensional clustering method based on the Gram--Schmidt algorithm are applied to members of each family to remove dynamic redundancy in their domain movements. Representative domain movements are described in terms of domains, hinge axes and hinge-bending residues using the DynDom program. The results show that within an average family of 11.5 members, there are on average only 1.31 different domain movements indicating a high redundancy in the movements these structures represent. This verifies earlier findings that domain movements are usually highly controlled. Despite the removal of this considerable redundancy, the process has resulted in double the number of domain movements stored in the user-created database. The data are organized in a relational database with a web-interface. Availability: The database can be browsed and searched at http://www.cmp.uea.ac.uk/dyndom Contact: sjh@cmp.uea.ac.uk