Search Options Explanation of Output Data
Selection of Long Coiled-Coil Proteins Release History and Updates
Prediction Programs Used Arabidopsis Database User Survey

Search Options

The ARABI-COIL search form provides several search options to identify coiled-coil proteins of interest for the user:

Refining Search Options

Length of Sequence

Length of Coiled-Coil Domain

Coiled-Coil Coverage

This feature allows the user to pre-select a certain coiled-coil domain structure, e.g. N-terminal or C-terminal coiled-coil domains.

Number of Transmembrane Domains

Predicted Localization

Explanation of Output Data

The details page for each protein entry provides the user with the following information about the protein:

General Information

Coiled-Coil Prediction Data

Transmembrane Properties

Predicted Localization

Predictions for the following localizations are included in the Arabi-Coil database:

All probability scores for targeting predictions are in the range of 0 (low probability) to 1 (high probability). Scores for ChloroP (0.4 - 0.6 range in raw output) were adjusted to 0 -1 range for better comparability. Hits in the PredictNLS database were given a score of 1.

Results above cut-off values for two confidence levels of scores at 0.5 (low confidence) and 0.75 (high confidence) are marked in yellow and red, respectively.

Selection of Long Coiled-Coil Proteins


Prediction Programs Used

The following programs and prediction servers were used to generate data for the Arabi-Coil Database.

MultiCoil - prediction of two- and three-stranded coiled-coils
Wolf, E., Kim, P.S., and Berger, B. (1997): MultiCoil: A Program for Predicting Two- and Three-Stranded Coiled Coils. Protein Sci. 6: 1179-1189.

Center for Biological Sequence Analysis Prediction Servers

ChloroP 1.1 - prediction of chloroplast transit peptide
Emanuelsson, O., Nielsen, H., and von Heijne, G. (1999): ChloroP, a neural network-based method for predicting chloroplast transit peptides and their cleavage sites. Protein Sci. 8: 978-984.

SignalP V2.0 - prediction of signal peptide
Neural Network:
Nielsen, H., Engelbrecht, J., Brunak, S., and von Heijne, G. (1997): A neural network method for identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites. Int. J. Neural. Syst. 8: 581-599.

Hidden Markov Model:
Nielsen, H., and Krogh, A. (1998): Prediction of signal peptides and signal anchors by a hidden Markov model. Proc. Int. Conf. Intell. Syst. Mol. Biol. 6: 122-130.

TargetP v1.01 - prediction of subcellular location
Emanuelsson, O., Nielsen, H., Brunak, S., and von Heijne, G. (2000): Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J. Mol. Biol. 300: 1005-1016.

TMHMM (v. 2.0) - prediction of transmembrane helices
Krogh, A., Larsson, B., von Heijne, G., and Sonnhammer, E.L.L. (2001): Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. J. Mol. Biol. 305: 567-580.

Other Prediction Servers

HMMTOP - prediction of transmembrane helices and topology
Tusnády, G.E., and Simon, I. (1998): Principles Governing Amino Acid Composition of Integral Membrane Proteins: Applications to Topology Prediction. J. Mol. Biol. 283: 489-506.

MITOPROT - prediction of mitochondrial targeting
Claros, M.G., and Vincens, P (1996). Computational method to predict mitochondrially imported proteins and their targeting sequences. Eur. J. Biochem. 241: 779-786.

Predotar - prediction of mitochondrial and plastid targeting sequences

PredictNLS server - prediction of nuclear localization signals
Cokol, M., Nair, R., and Rost, B. (2000): Finding Nuclear localization signals. EMBO Rep. 1: 411-415.

PSORT - prediction of protein sorting signals and localization
Nakai, K., and Horton, P. (1999): PSORT: a program for detecting the sorting signals of proteins and predicting their subcellular localization. Trends Biochem. Sci. 24: 34-35.

Release History and Updates

version 1.0 - released Nov. 04, 2003


Annkatrin Rose, Sankaraganesh Manikantan, Shannon J. Schraegle, Michael A. Maloy, Eric A. Stahlberg, and Iris Meier (2004). Genome-wide Identification of Arabidopsis Coiled-Coil Proteins and Establishment of the ARABI-COIL Database. Plant Physiol. 134, 927-939. - Abstract at NCBI PubMed

A.R., I.M. (corresponding author): Department of Plant Cellular and Molecular Biology and Plant Biotechnology Center, The Ohio State University, 1060 Carmack Road, Columbus, OH 43210, USA

S.M., S.J.S. (webmaster), M.A.M., E.A.S.: Ohio Supercomputer Center, 1224 Kinnear Road, Columbus, OH 43212, USA

The ARABI-COIL database was made possible with support from the National Science Foundation Project 2010 and the Ohio Supercomputer Center.