Bioinformatics Software Development Projects

Genome-wide identification of Arabidopsis coiled-coil proteins and establishment of the ARABI-COIL database

Principal Investigator: Iris Meier, Ohio State University
CoPI: Eric Stahlberg, OSC
Funding Agency: National Science Foundation

Description: Increasing evidence demonstrates the importance of long coiled-coil proteins for the spatial organization of cellular processes. Although several protein classes with long coiled-coil domains have been studied in animals and yeast, our knowledge about plant long coiled-coil proteins is very limited. The repeat nature of the coiled-coil sequence motif often prevents the simple identification of homologs of animal coiled-coil proteins by generic sequence similarity searches. As a consequence, counterparts of many animal proteins with long coiled-coil domains, like lamins, golgins, or microtubule organization center components, have not been identified yet in plants. Here, all Arabidopsis proteins predicted to contain long stretches of coiled-coil domains were identified by applying the algorithm MultiCoil to a genome-wide screen. A searchable protein database, ARABI-COIL (, was established that integrates information on number, size, and position of predicted coiled-coil domains with subcellular localization signals, transmembrane domains, and available functional annotations. ARABI-COIL serves as a tool to sort and browse Arabidopsis long coiled-coil proteins to facilitate the identification and selection of candidate proteins of potential interest for specific research areas. Using the database, candidate proteins were identified for Arabidopsis membrane-bound, nuclear, and organellar long coiled-coil proteins.

Click here for the paper as published in the March 2004 journal of Plant Physiology.

Ethan Wolf, Peter S. Kim, and Bonnie Berger, "MultiCoil: A Program for Predicting Two- and Three-Stranded Coiled Coils", Protein Science 6:1179-1189. June 1997.

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