KFC Server: interactive forecasting of protein interaction hot spots.

132Citations
Citations of this article
77Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Darnell, S. J., LeGault, L., & Mitchell, J. C. (2008). KFC Server: interactive forecasting of protein interaction hot spots. Nucleic Acids Research, 36(Web Server issue). https://doi.org/10.1093/nar/gkn346

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free