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Updated: May 6, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Negatome 2.0: a database of non-interacting proteins derived by literature mining, manual annotation and protein
Philipp Blohm1, Goar Frishman, Pawel Smialowski
1Institute for Bioinformatics and Systems Biology/MIPS, HMGU - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764 Neuherberg, Germany, Clueda AG, Elsenheimerstraße 59, 80687 Munich, Germany and Department of Genome Oriented Bioinformatics, Technische Universitaet Muenchen Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.
Abstract:
Knowledge about non-interacting proteins (NIPs) is important for training the algorithms to predict protein-protein interactions (PPIs) and for assessing the false positive rates of PPI detection efforts. We present the second version of Negatome, a database of proteins and protein domains that are unlikely to engage in physical interactions (available online at http://mips.helmholtz-muenchen.de/proj/ppi/negatome). Negatome is derived by manual curation of literature and by analyzing three-dimensional structures of protein complexes. The main methodological innovation in Negatome 2.0 is the utilization of an advanced text mining procedure to guide the manual annotation process. Potential non-interactions were identified by a modified version of Excerbt, a text mining tool based on semantic sentence analysis. Manual verification shows that nearly a half of the text mining results with the highest confidence values correspond to NIP pairs. Compared to the first version the contents of the database have grown by over 300%.
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