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Updated: Jul 3, 2026

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
Published on: July 16, 2017
MetalDetector: a web server for predicting metal-binding sites and disulfide bridges in proteins from sequence
Marco Lippi1, Andrea Passerini, Marco Punta
1Dipartimento di Sistemi e Informatica, Machine Learning and Neural Networks Group, Università degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy.
Unlabelled:
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.
Supplementary Information:
Details and data can be found at http://metaldetector.dsi.unifi.it/help.php.
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