Predicting proteolytic sites in extracellular proteins: only halfway there.
Bioinformatics
; 24(8): 1049-55, 2008 Apr 15.
Article
in En
| MEDLINE
| ID: mdl-18321887
ABSTRACT
MOTIVATION Many secretory proteins are synthesized as inactive precursors that must undergo post-translational proteolysis in order to mature and become active. In the current study, we address the challenge of sequence-based discovery of proteolytic sites in secreted proteins using machine learning. RESULTS:
The results revealed that only half of the extracellular proteolytic sites are currently annotated, leaving over 3600 unannotated ones. Furthermore, we have found that only 6% of the unannotated sites are similar to known proteolytic sites, whereas the remaining 94% do not share significant similarity with any annotated proteolytic site. The computational challenges in these two cases are very different. While the precision in detecting the former group is close to perfect, only a mere 22% of the latter group were detected with a precision of 80%. The applicability of the classifier is demonstrated through members of the FGF family, in which we verified the conservation of physiologically-relevant proteolytic sites in homologous proteins.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Extracellular Matrix Proteins
/
Sequence Alignment
/
Sequence Analysis, Protein
/
Models, Chemical
Type of study:
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
Bioinformatics
Journal subject:
INFORMATICA MEDICA
Year:
2008
Document type:
Article
Affiliation country:
Israel
Country of publication:
ENGLAND
/
ESCOCIA
/
GB
/
GREAT BRITAIN
/
INGLATERRA
/
REINO UNIDO
/
SCOTLAND
/
UK
/
UNITED KINGDOM