PrOCoil - Predicting the Oligomerization of Coiled Coil Proteins

We have developed an SVM-based classification method for predicting whether a given coiled coil sequence is a trimer or dimer (assuming that it is one of both). This method also allows for a deep analysis of the sequence which residues are mainly responsible for the outcome. The software is available as an R package procoil and as a simple-to-use Web application.

Important Note: the prediction models have been updated with the release of version 2.0.0 of the PrOCoil R package. If you want to use the prediction models as published by Mahrenholz et al. (2011), please follow the instructions in Section 5.5.3 of the user manual. The data provided on the PrOCoil data page are still the data on which the previous models were trained. An update of the data and a publication about PrOCoil v2 are currently in preparation.


The R package procoil is available from Bioconductor. The current version of the package is 2.0.0 and has been released as part of Bioconductor 3.3 on May 4, 2016. To install procoil, follow the simple standard procedure for installing Bioconductor packages, i.e. enter the following into your R session:
Please note that Bioconductor 3.3 requires an R version ≥ 3.3.0. The current development version of the package is 2.1.0.

Getting started

To use the package, enter "library(procoil)" in your R session. To get a basic introduction, enter "help(procoil)" or open the user manual by entering "vignette("procoil")".


  1. User Manual: PDF (also contains documentation of Web interface)
  2. Reference Manual: PDF

How to cite PrOCoil

If you use PrOCoil for research that is published later, you are kindly asked to cite it as follows:
C. C. Mahrenholz, I. G. Abfalter, U. Bodenhofer, R. Volkmer, and S. Hochreiter. Complex networks govern coiled coil oligomerization - predicting and profiling by means of a machine learning approach. Mol. Cell. Proteomics 10(5):M110.004994, 2011. DOI: 10.1074/mcp.M110.004994