ModLink+: improving fold recognition by using protein-protein interactions.
BACKGROUND
Several strategies have been developed to predict the fold of a target protein sequence, most of which are based on aligning the target sequence to other sequences of known structure. Previously, we demonstrated that the consideration of protein-protein interactions significantly increases the accuracy of fold assignment compared with PSI-BLAST sequence comparisons. A drawback of our method was the low number of proteins to which a fold could be assigned. Here, we present an improved version of the method that addresses this limitation. We also compare our method to other state-of-the-art fold assignment methodologies.


RESULTS
Our approach (ModLink+) has been tested on 3716 proteins with domain folds classified in the Structural Classification Of Proteins (SCOP) as well as known interacting partners in the Database of Interacting Proteins (DIP). For this test set, the ratio of success [positive predictive value (PPV)] on fold assignment increases from 75% for PSI-BLAST, 83% for HHSearch and 81% for PRC to >90% for ModLink+at the e-value cutoff of 10(-3). Under this e-value, ModLink+can assign a fold to 30-45% of the proteins in the test set, while our previous method could cover <25%. When applied to 6384 proteins with unknown fold in the yeast proteome, ModLink+combined with PSI-BLAST assigns a fold for domains in 3738 proteins, while PSI-BLAST alone covers only 2122 proteins, HHSearch 2969 and PRC 2826 proteins, using a threshold e-value that would represent a PPV >82% for each method in the test set.


BACKGROUND
The ModLink+server is freely accessible in the World Wide Web at http://sbi.imim.es/modlink/.


BACKGROUND
Supplementary data are available at Bioinformatics online.
Structural Bioinformatics Lab (GRIB-IMIM), Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona (PRBB), Barcelona, Catalonia, Spain. boliva@imim.es
Oriol
O
Fornes
Ramon
R
Aragues
Jordi
J
Espadaler
Marc A
MA
Marti-Renom
Andrej
A
Sali
Baldo
B
Oliva
D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D017510:Protein Folding; D054730:Protein Interaction Domains and Motifs; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D020539:Sequence Analysis, Protein
D011506:Proteins