LOGICOIL-multi-state prediction of coiled-coil oligomeric state

Thomas L. Vincent, Peter J. Green, Derek N. Woolfson*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

82 Citations (Scopus)

Abstract

Motivation: The coiled coil is a ubiquitous alpha-helical protein-structure domain that directs and facilitates protein-protein interactions in a wide variety of biological processes. At the protein-sequence level, the coiled coil is readily recognized via a conspicuous heptad repeat of hydrophobic and polar residues. However, structurally coiled coils are more complicated, existing in a wide range of oligomer states and topologies. As a consequence, predicting these various states from sequence remains an unmet challenge.

Results: This work introduces LOGICOIL, the first algorithm to address the problem of predicting multiple coiled-coil oligomeric states from protein-sequence information alone. By covering > 90% of the known coiled-coil structures, LOGICOIL is a net improvement compared with other existing methods, which achieve a predictive coverage of similar to 31% of this population. This leap in predictive power offers better opportunities for genome-scale analysis, and analyses of coiled-coil containing protein assemblies.

Original languageEnglish
Pages (from-to)69-76
Number of pages8
JournalBioinformatics
Volume29
Issue number1
DOIs
Publication statusPublished - Jan 2013

Keywords

  • CLASSIFICATION PROBLEMS
  • PACKING
  • GENE SELECTION
  • PROGRAM
  • PROTEIN STRUCTURES
  • CANCER CLASSIFICATION
  • MULTINOMIAL REGRESSION
  • BURIED POLAR RESIDUES
  • GCN4 LEUCINE-ZIPPER
  • BAYESIAN VARIABLE SELECTION

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  • 8092 EPSRC D063485

    Nason, G. P. (Principal Investigator)

    1/08/16 → …

    Project: Research

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