SHRIMP

By | September 22, 2011

SHRIMP
Compared with globular proteins, transmembrane proteins are surrounded by a more intricate environment and, consequently, amino acid composition varies between the different compartments. Existing algorithms for homology detection are generally developed with globular proteins in mind and may not be optimal to detect distant homology between transmembrane proteins. Here, we introduce a new profile-profile based alignment method for remote homology detection of transmembrane proteins in a hidden Markov model framework that takes advantage of the sequence constraints placed by the hydrophobic interior of the membrane. We expect that, for distant membrane protein homologs, even if the sequences have diverged too far to be recognized, the hydrophobicity pattern and the transmembrane topology are better conserved. By using this information in parallel with sequence information, we show that both sensitivity and specificity can be substantially improved for remote homology detection in two independent test sets. In addition, we show that alignment quality can be improved for the most distant homologs in a public dataset of membrane protein structures. Applying the method to the Pfam domain database, we are able to suggest new putative evolutionary relationships for a few relatively uncharacterized protein domain families, of which several are confirmed by other methods. The method is called Searcher for Homology Relationships of Integral Membrane Proteins (SHRIMP) and is available for download at http://www.sbc.su.se/shrimp/.

SHRIMP-OPM
This service runs SHRIMP against alpha-helical membrane proteins found in the OPM database ( http://opm.phar.umich.edu ).
The service is implemented as an asynchronous service where the user submits a job, retrieves a job ID. This job ID can then be used to poll the server to receive a status message. When the job has completed, the result can be fetched.

Name
SHRIMP
Documentation
http://www.sbc.su.se/shrimp
Protocol
SOAP
WSDL
Endpoint
http://wsdl.sbc.su.se/cgi-bin/shrimp.cgi
Topic
Biology
Type
Tags
, , , ,
Description

SHRIMP Compared with globular proteins, transmembrane proteins are surrounded by a more intricate environment and, consequently, amino acid composition varies [...]

Further information

SHRIMP
Compared with globular proteins, transmembrane proteins are surrounded by a more intricate environment and, consequently, amino acid composition varies between the different compartments. Existing algorithms for homology detection are generally developed with globular proteins in mind and may not be optimal to detect distant homology between transmembrane proteins. Here, we introduce a new profile-profile based alignment method for remote homology detection of transmembrane proteins in a hidden Markov model framework that takes advantage of the sequence constraints placed by the hydrophobic interior of the membrane. We expect that, for distant membrane protein homologs, even if the sequences have diverged too far to be recognized, the hydrophobicity pattern and the transmembrane topology are better conserved. By using this information in parallel with sequence information, we show that both sensitivity and specificity can be substantially improved for remote homology detection in two independent test sets. In addition, we show that alignment quality can be improved for the most distant homologs in a public dataset of membrane protein structures. Applying the method to the Pfam domain database, we are able to suggest new putative evolutionary relationships for a few relatively uncharacterized protein domain families, of which several are confirmed by other methods. The method is called Searcher for Homology Relationships of Integral Membrane Proteins (SHRIMP) and is available for download at http://www.sbc.su.se/shrimp/.

SHRIMP-OPM
This service runs SHRIMP against alpha-helical membrane proteins found in the OPM database ( http://opm.phar.umich.edu ).
The service is implemented as an asynchronous service where the user submits a job, retrieves a job ID. This job ID can then be used to poll the server to receive a status message. When the job has completed, the result can be fetched.

Original source
BioCatalogue

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