Journal
BIOINFORMATICS
Volume 24, Issue 18, Pages 2094-2095Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btn371
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Funding
- National Institutes of Health (NIH) in the USA [R01-GM079767, R01-LM07329, U54-GM75026]
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The web server MetalDetector classifies histidine residues in proteins into one of two states (free or metal bound) and cysteines into one of three states (free, metal bound or disulfide bridged). A decision tree integrates predictions from two previously developed methods (DISULFIND and Metal Ligand Predictor). Cross-validated performance assessment indicates that our server predicts disulfide bonding state at 88.6% precision and 85.1% recall, while it identifies cysteines and histidines in transition metal-binding sites at 79.9% precision and 76.8% recall, and at 60.8% precision and 40.7% recall, respectively.
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