procoil
"PrOCoil" is a machine learning-based software tool developed to advance our understanding of the coiled-coil motif. A structural feature prevalent in proteins influences their oligomerization—the process by which multiple alpha-helices assemble to form a coiled-coil. Despite extensive characterization of coiled-coil structures, the specific rules governing their oligomerization, particularly the formation of two- and three-stranded coiled coils, remained elusive.
By analyzing weighted amino acid patterns, PrOCoil identifies and elucidates these rules, offering new insights into the determinants of coiled-coil stoichiometry. Notably, the tool highlights the significant role of sequence positions previously considered irrelevant to coiled-coil interactions, revealing their undeniable impact on oligomerization.
Additionally, PrOCoil provides a visualization feature demonstrating how each amino acid in a sequence contributes to the overall oligomeric tendency of a coiled-coil. This capability is instrumental in demystifying the oligomerization behavior of complex proteins, such as the yeast transcription factor GCN4. PrOCoil's analysis presents GCN4 as a hybrid entity with dimers and trimers characteristics supported by theoretical and experimental evidence.
Topic
Protein folds and structural domains;Proteins;Structural biology
Detail
Operation: Protein structure prediction
Software interface: Command-line user interface,Library
Language: R
License: GNU General Public License, version 2
Cost: Free
Version name: 2.30.0
Credit: The Manchot Foundation, the GlaxoSmithKline Foundation, the Charité Medical School.
Input: -
Output: -
Contact: Ulrich Bodenhofer bodenhofer@bioinf.jku.@
Collection: -
Maturity: Stable
Publications
- Complex networks govern coiled-coil oligomerization--predicting and profiling by means of a machine learning approach.
- Mahrenholz CC, et al. Complex networks govern coiled-coil oligomerization--predicting and profiling by means of a machine learning approach. Complex networks govern coiled-coil oligomerization--predicting and profiling by means of a machine learning approach. 2011; 10:M110.004994. doi: 10.1074/mcp.M110.004994
- https://doi.org/10.1074/mcp.M110.004994
- PMID: 21311038
- PMC: PMC3098589
Download and documentation
Source: https://bioconductor.org/packages/release/bioc/src/contrib/procoil_2.30.0.tar.gz
Documentation: https://bioconductor.org/packages/release/bioc/manuals/procoil/man/procoil.pdf
Home page: http://bioconductor.org/packages/release/bioc/html/procoil.html
< Back to DB search