| Literature DB >> 16301202 |
Jean-Christophe Gelly1, Alexandre G de Brevern, Serge Hazout.
Abstract
MOTIVATION: The object of this study is to propose a new method to identify small compact units that compose protein three-dimensional structures. These fragments, called 'protein units (PU)', are a new level of description to well understand and analyze the organization of protein structures. The method only works from the contact probability matrix, i.e. the inter Calpha-distances translated into probabilities. It uses the principle of conventional hierarchical clustering, leading to a series of nested partitions of the 3D structure. Every step aims at dividing optimally a unit into 2 or 3 subunits according to a criterion called 'partition index' assessing the structural independence of the subunits newly defined. Moreover, an entropy-derived squared correlation R is used for assessing globally the protein structure dissection. The method is compared to other splitting algorithms and shows relevant performance. AVAILABILITY: An Internet server with dedicated tools is available at http://www.ebgm.jussieu.fr/~gelly/Mesh:
Substances:
Year: 2005 PMID: 16301202 DOI: 10.1093/bioinformatics/bti773
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937