Gibbs sampling and helix-cap motifs

Erik Kruus, Peter Thumfort, Chao Tang, Ned S. Wingreen

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Protein backbones have characteristic secondary structures, including α-helices and β-sheets. Which structure is adopted locally is strongly biased by the local amino acid sequence of the protein. Accurate (probabilistic) mappings from sequence to structure are valuable for both secondary-structure prediction and protein design. For the case of α-helix caps, we test whether the information content of the sequence-structure mapping can be self-consistently improved by using a relaxed definition of the structure. We derive helix-cap sequence motifs using database helix assignments for proteins of known structure. These motifs are refined using Gibbs sampling in competition with a null motif. Then Gibbs sampling is repeated, allowing for frameshifts of ±1 amino acid residue, in order to find sequence motifs of higher total information content. All helix-cap motifs were found to have good generalization capability, as judged by training on a small set of non-redundant proteins and testing on a larger set. For overall prediction purposes, frameshift motifs using all training examples yielded the best results. Frameshift motifs using a fraction of all training examples performed best in terms of true positives among top predictions. However, motifs without frameshifts also performed well, despite a roughly one-third lower total information content.

Original languageEnglish (US)
Pages (from-to)5343-5353
Number of pages11
JournalNucleic acids research
Volume33
Issue number16
DOIs
StatePublished - 2005

All Science Journal Classification (ASJC) codes

  • Genetics

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