Membrane protein prediction methods

Marco Punta, Lucy R. Forrest, Henry Bigelow, Andrew Kernytsky, Jinfeng Liu, Burkhard Rost

Research output: Contribution to journalArticlepeer-review

107 Scopus citations

Abstract

We survey computational approaches that tackle membrane protein structure and function prediction. While describing the main ideas that have led to the development of the most relevant and novel methods, we also discuss pitfalls, provide practical hints and highlight the challenges that remain. The methods covered include: sequence alignment, motif search, functional residue identification, transmembrane segment and protein topology predictions, homology and ab initio modeling. In general, predictions of functional and structural features of membrane proteins are improving, although progress is hampered by the limited amount of high-resolution experimental information available. While predictions of transmembrane segments and protein topology rank among the most accurate methods in computational biology, more attention and effort will be required in the future to ameliorate database search, homology and ab initio modeling.

Original languageEnglish
Pages (from-to)460-474
Number of pages15
JournalMethods
Volume41
Issue number4
DOIs
StatePublished - Apr 2007
Externally publishedYes

Keywords

  • Alignments
  • Homology modeling
  • Membrane proteins
  • Protein function prediction
  • Protein structure prediction
  • Transmembrane segment prediction
  • ab initio modeling

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