PRALINETM: a strategy for improved multiple alignment of transmembrane proteins

Walter Pirovano, K Anton Feenstra, Jaap Heringa

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

MOTIVATION: Membrane-bound proteins are a special class of proteins. The regions that insert into the cell-membrane have a profoundly different hydrophobicity pattern compared with soluble proteins. Multiple alignment techniques use scoring schemes tailored for sequences of soluble proteins and are therefore in principle not optimal to align membrane-bound proteins.

RESULTS: Transmembrane (TM) regions in protein sequences can be reliably recognized using state-of-the-art sequence prediction techniques. Furthermore, membrane-specific scoring matrices are available. We have developed a new alignment method, called PRALINETM, which integrates these two features to enhance multiple sequence alignment. We tested our algorithm on the TM alignment benchmark set by Bahr et al. (2001), and showed that the quality of TM alignments can be significantly improved compared with the quality produced by a standard multiple alignment technique. The results clearly indicate that the incorporation of these new elements into current state-of-the-art alignment methods is crucial for optimizing the alignment of TM proteins.

AVAILABILITY: A webserver is available at http://www.ibi.vu.nl/programs/pralinewww.

Original languageEnglish
Pages (from-to)492-7
Number of pages6
JournalBioinformatics
Volume24
Issue number4
DOIs
Publication statusPublished - 15 Feb 2008

Keywords

  • Algorithms
  • Amino Acid Sequence
  • Computational Biology
  • Membrane Proteins
  • Molecular Sequence Data
  • Sequence Alignment
  • Journal Article
  • Research Support, Non-U.S. Gov't

Fingerprint

Dive into the research topics of 'PRALINETM: a strategy for improved multiple alignment of transmembrane proteins'. Together they form a unique fingerprint.

Cite this