Skip Navigation


Bioinformatics Advance Access originally published online on February 12, 2004
This Article
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow FREE Full Text (Screen PDF)
Right arrow Supplementary data
Right arrow All Versions of this Article:
20/9/1373    most recent
bth095v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (31)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Andreini, C.
Right arrow Articles by Rosato, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Andreini, C.
Right arrow Articles by Rosato, A.
Social Bookmarking
 Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Bioinformatics 20(9) © Oxford University Press 2004; all rights reserved.

A hint to search for metalloproteins in gene banks

Claudia Andreini 1,2, Ivano Bertini 1,2,* and Antonio Rosato 1,2

1 Magnetic Resonance Center (CERM) and 2 Department of Chemistry, University of Florence, 50019 Sesto Fiorentino, Italy

Received on July 9, 2003; revised on November 12, 2003; accepted on December 9, 2003
Advance Access Publication February 12, 2004

Motivation: With the advent of genome sequencing, a huge database of protein primary sequences has been accumulating. In parallel, a number of tools to investigate and expand upon this information, e.g. reconstructing and building relationships between protein families and superfamilies, have been developed. Metalloproteins are proteins capable of binding one or more metal ions, which are required for their biological function or for regulation of their activities or for structural purposes. Sometimes, metal binding can be observed in vitro but not be physiologically relevant. At present, there is a lack of specific tools to address the matter of the identification of metalloproteins in databases of gene sequences.

Results: In the present work, an approach exploiting metal-binding patterns (MBPs) of metalloproteins present in the Protein Data Bank to search gene banks for new metalloproteins is presented and applied to copper proteins. Nearly 100 different MBPs have been identified and then used for subsequent applications. The ensemble of sequences of the whole PDB is used to assess the potentiality and limits of the method and to identify levels of confidence for the predictions output by the search. It appears that copper-binding capabilities are identified with a confidence >90% when the percentage of identical amino acids aligned around the MBP by PHI-BLAST is at least 20% with respect to the entire protein domain length. If this percentage is between 10% and 20%, the level of confidence is ~50%. Application of the methodology to the entire genome sequences of Pyrococcus furiosus, Escherichia coli, Drosophila melanogaster and Homo sapiens suggests some differentiation between prokaryotes and eukaryotes.

Supplementary information: A table reporting statistics on the MBP identified; a list of all hits retrieved for the four organisms considered; a figure showing the number of hits for the four organisms as a function of IdGlobal.

Contact: bertini{at}cerm.unifi.it

* To whom correspondence should be addressed.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
BioinformaticsHome page
A. J. Bordner
Predicting small ligand binding sites in proteins using backbone structure
Bioinformatics, December 15, 2008; 24(24): 2865 - 2871.
[Abstract] [Full Text] [PDF]


Home page
BioinformaticsHome page
N. Shu, T. Zhou, and S. Hovmoller
Prediction of zinc-binding sites in proteins from sequence
Bioinformatics, March 15, 2008; 24(6): 775 - 782.
[Abstract] [Full Text] [PDF]



Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.