Predicting specificity in bZIP coiled-coil protein interactions.

Jessica H Fong, Amy E Keating, Mona Singh

Journal: Genome biology 2005;5(2):R11

PMID: 14759261

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Abstract

We present a method for predicting protein-protein interactions mediated by the coiled-coil motif. When tested on interactions between nearly all human and yeast bZIP proteins, our method identifies 70% of strong interactions while maintaining that 92% of predictions are correct. Furthermore, cross-validation testing shows that including the bZIP experimental data significantly improves performance. Our method can be used to predict bZIP interactions in other genomes and is a promising approach for predicting coiled-coil interactions more generally.

Address: Computer Science Department and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Olden Street, Princeton, NJ 08544, USA.

DOI: 10.1186/gb-2004-5-2-r11

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MeSH Terms: Amino Acid Motifs, Basic-Leucine Zipper Transcription Factors, Computational Biology, DNA-Binding Proteins, Fungal Proteins, G-Box Binding Factors, Humans, Models, Molecular, Protein Binding, Protein Structure, Secondary, Reproducibility of Results, Static Electricity, Transcription Factors