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PMID: 14764543 Published · ppublish English Comparative Study Evaluation Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S. Validation Study

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

Bioinformatics (Oxford, England) ·Vol. 20 ·No. 7 ·2004-05-01 ·Pages 1087-96

Arakaki AK, Zhang Y, Skolnick J

Abstract

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. 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 A coordinate root mean square deviation from the native structure, a quality that is reachable using state of the art protein structure prediction algorithms. See http://www.bioinformatics.buffalo.edu/resources/aft/

MeSH Terms
Algorithms Amino Acid Sequence Binding Sites Computer Simulation Databases, Protein Enzymes/chemistry,classification Escherichia coli Proteins/chemistry,classification Models, Molecular Molecular Sequence Data Protein Binding Protein Conformation Proteins/chemistry,classification Reproducibility of Results Sensitivity and Specificity Sequence Alignment/methods Sequence Analysis, Protein/methods Structure-Activity Relationship
Chemicals
Enzymes Escherichia coli Proteins Proteins
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Arakaki Adrian K
Center of Excellence in Bioinformatics, University at Buffalo, 901 Washington Street, Buffalo, NY 14203-1199, USA.
Zhang Yang
Skolnick Jeffrey
Article Info
Journal
Bioinformatics (Oxford, England)
Abbr.
Bioinformatics
ISSN
1367-4803
Published
2004-05-01
Epub
2004-00-05
Pages
1087-96
Language
English
Region
England
NLM ID
9808944
Subset
IM
Grants
NIGMS NIH HHS · GM 48835 · United States
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