KFC Server: interactive forecasting of protein interaction hot spots
| Autor: | Steven J. Darnell, Julie C. Mitchell, Laura Hobbes Legault |
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| Rok vydání: | 2008 |
| Předmět: |
Models
Molecular Binding free energy Protein Conformation Real-time computing Biology 010402 general chemistry Bioinformatics 01 natural sciences 03 medical and health sciences Software Artificial Intelligence Protein Interaction Mapping Genetics Computational analysis 030304 developmental biology Internet 0303 health sciences Binding Sites business.industry A protein Articles 0104 chemical sciences Visualization Multiprotein Complexes business |
| Zdroj: | Nucleic Acids Research |
| ISSN: | 1362-4962 0305-1048 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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