Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Prediction of membrane-protein topology from first principles
Stockholm University.
Stockholm University.
Stockholm University.
Stockholm University.ORCID iD: 0000-0002-2734-2794
Show others and affiliations
2008 (English)In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 105, no 20, 7177-7781 p.Article in journal (Refereed) Published
Abstract [en]

The current best membrane-protein topology-prediction methods are typically based on sequence statistics and contain hundreds of parameters that are optimized on known topologies of membrane proteins. However, because the insertion of transmembrane helices into the membrane is the outcome of molecular interactions among protein, lipids and water, it should be possible to predict topology by methods based directly on physical data, as proposed >20 years ago by Kyte and Doolittle. Here, we present two simple topology-prediction methods using a recently published experimental scale of position-specific amino acid contributions to the free energy of membrane insertion that perform on a par with the current best statistics-based topology predictors. This result suggests that prediction of membrane-protein topology and structure directly from first principles is an attainable goal, given the recently improved understanding of peptide recognition by the translocon.

Place, publisher, year, edition, pages
2008. Vol. 105, no 20, 7177-7781 p.
Keyword [en]
bioinformatics, membrane insertion, topology prediction, translocon, biological hydrophobicity scale
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:kth:diva-82618DOI: 10.1073/pnas.0711151105ISI: 000256162900015PubMedID: 18477697OAI: oai:DiVA.org:kth-82618DiVA: diva2:498477
Note
QC 20120217Available from: 2012-02-12 Created: 2012-02-12 Last updated: 2017-12-07Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Authority records BETA

Lindahl, Erik

Search in DiVA

By author/editor
Lindahl, Erik
In the same journal
Proceedings of the National Academy of Sciences of the United States of America
Bioinformatics and Systems Biology

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 55 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf