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Nucleic Acids Research Advance Access published online on June 6, 2008
Nucleic Acids Research, doi:10.1093/nar/gkn346
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Web Server Issue

KFC Server: interactive forecasting of protein interaction hot spots

Steven J. Darnell1, Laura LeGault2 and Julie C. Mitchell1,3,*

1Department of Biochemistry, 2Department of Computer Sciences and 3Department of Mathematics, University of Wisconsin-Madison, Madison, WI 53706, USA

*To whom correspondence should be addressed. Tel: 608 890 0365; Fax: 608 262 3453; Email: jcmitchell{at}wisc.edu

Received January 31, 2008. Revised April 17, 2008. Accepted May 8, 2008.

The KFC Server is a web-based implementation of the KFC (Knowledge-based FADE and Contacts) model—a machine learning approach for the prediction of binding hot spots, or the subset of residues that account for most of a protein interface's; binding free energy. The server facilitates the automated analysis of a user submitted protein–protein or protein–DNA interface and the visualization of its hot spot predictions. For each residue in the interface, the KFC Server characterizes its local structural environment, compares that environment to the environments of experimentally determined hot spots and predicts if the interface residue is a hot spot. After the computational analysis, the user can visualize the results using an interactive job viewer able to quickly highlight predicted hot spots and surrounding structural features within the protein structure. The KFC Server is accessible at http://kfc.mitchell-lab.org.


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