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.

MetalDetector: a web server for predicting metal binding sites and disulfide bridges in proteins from sequence / M. Lippi;A. Passerini;M. Punta;B. Rost;P. Frasconi. - In: BIOINFORMATICS. - ISSN 1367-4803. - STAMPA. - 24:(2008), pp. 2094-2095. [10.1093/bioinformatics/btn371]

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

FRASCONI, PAOLO
2008

Abstract

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.
24
2094
2095
M. Lippi;A. Passerini;M. Punta;B. Rost;P. Frasconi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2158/386612
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