Wordprocessing

HMMerThread: detecting remote, functional conserved domains in entire genomes by combining relaxed sequence-database searches with fold recognition

Abstract:

Conserved domains in proteins are one of the major sources of functional information for experimental design and genome-level annotation. Though search tools for conserved domain databases such as Hidden Markov Models (HMMs) are sensitive in detecting conserved domains in proteins when they share sufficient sequence similarity, they tend to miss more divergent family members, as they lack a reliable statistical framework for the detection of low sequence similarity. We have developed a greatly improved HMMerThread algorithm that can detect remotely conserved domains in highly divergent sequences. HMMerThread combines relaxed conserved domain searches with fold recognition to eliminate false positive, sequence-based identifications. With an accuracy of 90%, our software is able to automatically predict highly divergent members of conserved domain families with an associated 3-dimensional structure. We give additional confidence to our predictions by validation across species. We have run HMMerThread searches on eight proteomes including human and present a rich resource of remotely conserved domains, which adds significantly to the functional annotation of entire proteomes. We find ∼4500 cross-species validated, remotely conserved domain predictions in the human proteome alone. As an example, we find a DNA-binding domain in the C-terminal part of the A-kinase anchor protein 10 (AKAP10), a PKA adaptor that has been implicated in cardiac arrhythmias and premature cardiac death, which upon stress likely translocates from mitochondria to the nucleus/nucleolus. Based on our prediction, we propose that with this HLH-domain, AKAP10 is involved in the transcriptional control of stress response. Further remotely conserved domains we discuss are examples from areas such as sporulation, chromosome segregation and signalling during immune response. The HMMerThread algorithm is able to automatically detect the presence of remotely conserved domains in proteins based on weak sequence similarity. Our predictions open up new avenues for biological and medical studies. Genome-wide HMMerThread domains are available at http://vm1-hmmerthread.age.mpg.de.

21423752

Projects: A1.3: Identification of crucial metabolic processes during hepatocyte pr..., A3.2: Cross-talk of signaling pathways and endocytic machinery in hepato..., A3.5: The impact of cell polarity on metabolism detoxification and endoc..., C2: Organization of the sinusoidal system and the liver lobule - referen..., C5: Structural changes and functional consequences of the liver lobular/..., C6: Organization and function of the sinusoidal system and the liver lob...

PLoS ONE
PLoS ONE 6(3): e17568
16th Nov 2010

Charles Richard Bradshaw, Vineeth Surendranath, Robert Henschel, Matthias Stefan Mueller, Bianca Hermine Habermann

help Authors

[Bianca Habermann]

help Attributions

None

help Scales


Not Specified
Views: 1538
  • Created: 24th Jun 2011 at 16:19
  • Last updated: 24th Oct 2013 at 16:19

Related items

Ajax-loader-large

Log in / Register

Need an account?
Sign up

Forgotten password?

Front Page

Virtual Liver Network

(v.0.22.0)

Related Projects and friends


Imprint Taverna workflow workbench myExperiment JWS Online ISATAB myGrid Sabio-RK BioPortal Semantic SBML

Powered by:

Ror-logo-32

Icons:
Silk icons 1.3
Crystal Clear icons