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


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