A Hybrid Evolutionary Approach for the Protein Classification Problem
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
| Hi-index | 3.84 |
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/