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Bioinformatics Advance Access originally published online on February 5, 2004
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Bioinformatics 20(7) © Oxford University Press 2004; all rights reserved.

Large-scale assessment of the utility of low-resolution protein structures for biochemical function assignment

Adrian K. Arakaki , Yang Zhang and Jeffrey Skolnick *

Center of Excellence in Bioinformatics, University at Buffalo, 901 Washington St, Buffalo, NY 14203–1199, USA

Received on August 19, 2003; revised on November 5, 2003; accepted on November 26, 2003
Advance Access Publication February 5, 2004

Motivation: Several protein function prediction methods employ structural features captured in three-dimensional (3D) descriptors of biologically relevant sites. These methods are successful when applied to high-resolution structures, but their detection ability in lower resolution predicted structures has only been tested for a few cases.

Results: A method that automatically generates a library of 3D functional descriptors for the structure-based prediction of enzyme active sites (automated functional templates, 593 in total for 162 different enzymes), based on functional and structural information automatically extracted from public databases, has been developed and evaluated using decoy structures. The applicability to predicted structures was investigated by analyzing decoys of varying quality, derived from enzyme native structures. For 35% of decoy structures, our method identifies the active site in models having 3–4 Å coordinate root mean square deviation from the native structure, a quality that is reachable using state of the art protein structure prediction algorithms.

Availability: See http://www.bioinformatics.buffalo.edu/resources/aft/

Contact: skolnick{at}buffalo.edu

* To whom correspondence should be addressed.


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