Noxclass: Prediction of Protein-protein Interaction Types.
From: Max-Planck-lnstitut für Informatik, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. hzhu@mpi-sb.mpg.de
BMC bioinformatics
- Publish Date: 2006
- ISSN: 1471-2105
- Volume: 7
- Issue:
- Pages: 27
- Medium: Internet
- Language: English
- Citation (JAMA): Zhu Hongbo, Domingues Francisco S, Sommer Ingolf, et al. Noxclass: Prediction of Protein-protein Interaction Types.. BMC Bioinformatics 2006;7:27
Abstract
BACKGROUND: Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. This has been investigated previously and classification approaches have been proposed. However, less attention has been devoted to distinguishing different types of biological interactions. These interactions are classified as obligate and non-obligate according to the effect of the complex formation on the stability of the protomers. So far no automatic classification methods for distinguishing obligate, non-obligate and crystal packing interactions have been made available. RESULTS: Six interface properties have been investigated on a dataset of 243 protein interactions. The six properties have been combined using a support vector machine algorithm, resulting in NOXclass, a classifier for distinguishing obligate, non-obligate and crystal packing interactions. We achieve an accuracy of 91.8% for the classification of these three types of interactions using a leave-one-out cross-validation procedure. CONCLUSION: NOXclass allows the interpretation and analysis of protein quaternary structures. In particular, it generates testable hypotheses regarding the nature of protein-protein interactions, when experimental results are not available. We expect this server will benefit the users of protein structural models, as well as protein crystallographers and NMR spectroscopists. A web server based on the method and the datasets used in this study are available at http://noxclass.bioinf.mpi-inf.mpg.de/.
Mesh Headings (Keywords): Algorithms, Artificial Intelligence, Binding Sites, Computer Simulation, Crystallography, Models, Chemical, Models, Molecular, Online Systems, Pattern Recognition, Automated, Protein Binding, Protein Conformation, Protein Interaction Mapping, Protein Structure, Quaternary, Proteins, Sequence Analysis, Protein, Software
Check for Full Text / PubMed Unique Identifier (PMID): 16423290
This abstract is part of PubMed, a service of the U.S. National Library of Medicine. PubMed includes more than 17 million citations from MEDLINE and other life science journals for biomedical articles. See Copyright and Disclaimers.
Linked medical terms appearing on this page are added by Healia to help readers find more information and are not part of the original PubMed document.
The data herein was last updated on July 8th, 2008 and may not reflect the most current and accurate data available from NLM.