Journal Article

MetalDetector: a web server for predicting metal-binding sites and disulfide bridges in proteins from sequence

Marco Lippi, Andrea Passerini, Marco Punta, Burkhard Rost and Paolo Frasconi

in Bioinformatics

Volume 24, issue 18, pages 2094-2095
Published in print September 2008 | ISSN: 1367-4803
Published online July 2008 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btn371
MetalDetector: a web server for predicting metal-binding sites and disulfide bridges in proteins from sequence

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Summary: 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.

Availability: Freely available at http://metaldetector.dsi.unifi.it

Contact: metaldetector@dsi.unifi.it

Supplementary Information: Details and data can be found at http://metaldetector.dsi.unifi.it/help.php

Journal Article.  1176 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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