期刊
NUCLEIC ACIDS RESEARCH
卷 36, 期 -, 页码 W265-W269出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkn346
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资金
- NLM NIH HHS [T15 LM007359, 5T15LM007359] Funding Source: Medline
The KFC Server is a web-based implementation of the KFC (Knowledge-based FADE and Contacts) modela machine learning approach for the prediction of binding hot spots, or the subset of residues that account for most of a protein interfaces; binding free energy. The server facilitates the automated analysis of a user submitted proteinprotein or proteinDNA 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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