Linked Life Data

18988691

Source:http://linkedlifedata.com/resource/pubmed/id/18988691

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2008-12-17
pubmed:abstractText
Computational prediction of signal peptides (SPs) and their cleavage sites is of great importance in computational biology; however, currently there is no available method capable of predicting reliably the SPs of archaea, due to the limited amount of experimentally verified proteins with SPs. We performed an extensive literature search in order to identify archaeal proteins having experimentally verified SP and managed to find 69 such proteins, the largest number ever reported. A detailed analysis of these sequences revealed some unique features of the SPs of archaea, such as the unique amino acid composition of the hydrophobic region with a higher than expected occurrence of isoleucine, and a cleavage site resembling more the sequences of gram-positives with almost equal amounts of alanine and valine at the position-3 before the cleavage site and a dominant alanine at position-1, followed in abundance by serine and glycine. Using these proteins as a training set, we trained a hidden Markov model method that predicts the presence of the SPs and their cleavage sites and also discriminates such proteins from cytoplasmic and transmembrane ones. The method performs satisfactorily, yielding a 35-fold cross-validation procedure, a sensitivity of 100% and specificity 98.41% with the Matthews' correlation coefficient being equal to 0.964. This particular method is currently the only available method for the prediction of secretory SPs in archaea, and performs consistently and significantly better compared with other available predictors that were trained on sequences of eukaryotic or bacterial origin. Searching 48 completely sequenced archaeal genomes we identified 9437 putative SPs. The method, PRED-SIGNAL, and the results are freely available for academic users at http://bioinformatics.biol.uoa.gr/PRED-SIGNAL/ and we anticipate that it will be a valuable tool for the computational analysis of archaeal genomes.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1741-0134
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
22
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
27-35
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Prediction of signal peptides in archaea.
pubmed:affiliation
Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Athens 15701, Greece. pbagos@biol.uoa.gr
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't