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Bioinformatics Advance Access published online on February 1, 2008
Bioinformatics, doi:10.1093/bioinformatics/btm618
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© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Prediction of Zinc-Binding Sites in Proteins from Sequence

Nanjiang Shu *, Tuping Zhou and Hovmöller Sven

Structural Chemistry, Arrhenius Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden

*To whom correspondence should be addressed. Dr. Nanjiang Shu, E-mail: nanjiang{at}struc.su.se


  Abstract

Motivation: Motivated by the abundance, importance and unique functionality of zinc, both biologically and physiologically, we have developed an improved method for the prediction of zinc-binding sites in proteins from their amino acid sequences.

Results: By combining support vector machine (SVM) and homology-based predictions, our method predicts zinc-binding Cys, His, Asp and Glu with 75% precision (86% for Cys and His only) at 50% recall according to a five-fold cross-validation on a non- redundant set of protein chains from the Protein Data Bank (PDB) (2727 chains, 235 of which bind zinc). Consequently, our method predicts zinc-binding Cys and His with 10% higher precision at different recall levels compared to a recently published method when tested in the same dataset.

Availability: The program is available for download at www.fos.su.se/~nanjiang/zincpred/download/.

Supplementary data: All supplementary data can be accessed at www.fos.su.se/~nanjiang/zincpred/suppliment

Associate Editor: prof. Burkhard Rost

Received on October 18, 2007; revised on December 9, 2007; accepted on December 11, 2007

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