<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fornes, O.</style></author><author><style face="normal" font="default" size="100%">Aragues, R.</style></author><author><style face="normal" font="default" size="100%">Espadaler, J.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author><author><style face="normal" font="default" size="100%">Oliva, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ModLink+: Improving fold recognition by using protein-protein interactions</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">protein folding</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=19357100</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;MOTIVATION: 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 to 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 3,716 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 (PPV) on fold assignment increases from 75% for PSI-BLAST, 83% for HHSearch and 81% for PRC to more than 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 less than 25%. When applied to 6,384 proteins with unknown fold in the yeast proteome, ModLink+ combined with PSI-BLAST assigns a fold for domains in 3,738 proteins, while PSI-BLAST alone only covers 2,122 proteins, HHSearch 2,969 and PRC 2,826 proteins, using a threshold e-value that would represent a PPV higher than 82% for each method in the test set. AVAILABILITY: The ModLink+ server is freely accessible in the World Wide Web at http://sbi.imim.es/modlink/. CONTACT: boliva@imim.es.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Journal article Bioinformatics (Oxford, England) Bioinformatics. 2009 Apr 8.&lt;/p&gt;</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Espadaler, J.</style></author><author><style face="normal" font="default" size="100%">Eswar, N.</style></author><author><style face="normal" font="default" size="100%">Querol, E.</style></author><author><style face="normal" font="default" size="100%">Aviles, F. X.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Oliva, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Prediction of enzyme function by combining sequence similarity and protein interactions</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid *Software Structure-Activity Relationship Substrate Specificity/genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence/physiology Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Automated Predictive Value of Tests Protein Interaction Mapping Proteins/analysis/metabolism Sequence Alignment Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein *Sequence Homology</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein Enzymes/analysis/*metabolism Fuzzy Logic Pattern Recognition</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=18505562</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">249</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: A number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners. RESULTS: The method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80% to 90% at 80% coverage when compared to PSI-BLAST. CONCLUSION: Our method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.</style></abstract><notes><style face="normal" font="default" size="100%">Espadaler, Jordi Eswar, Narayanan Querol, Enrique Aviles, Francesc X Sali, Andrej Marti-Renom, Marc A Oliva, Baldomero GM54762/GM/NIGMS NIH HHS/United States GM71790/GM/NIGMS NIH HHS/United States GM74929/GM/NIGMS NIH HHS/United States GM74945/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov’t England BMC bioinformatics BMC Bioinformatics. 2008 May 27;9:249.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Espadaler, J.</style></author><author><style face="normal" font="default" size="100%">Aragues, R.</style></author><author><style face="normal" font="default" size="100%">Eswar, N.</style></author><author><style face="normal" font="default" size="100%">M. A. Marti-Renom</style></author><author><style face="normal" font="default" size="100%">Querol, E.</style></author><author><style face="normal" font="default" size="100%">Aviles, F. X.</style></author><author><style face="normal" font="default" size="100%">Sali, A.</style></author><author><style face="normal" font="default" size="100%">Oliva, B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Detecting remotely related proteins by their interactions and sequence similarity</style></title><secondary-title><style face="normal" font="default" size="100%">Proc Natl Acad Sci U S A</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Protein Conformation Protein Folding Proteins/*genetics/*metabolism Proteomics/*methods *Sequence Homology</style></keyword><keyword><style  face="normal" font="default" size="100%">Protein *Evolution</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=15883372</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">20</style></number><volume><style face="normal" font="default" size="100%">102</style></volume><pages><style face="normal" font="default" size="100%">7151-6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The function of an uncharacterized protein is usually inferred either from its homology to, or its interactions with, characterized proteins. Here, we use both sequence similarity and protein interactions to identify relationships between remotely related protein sequences. We rely on the fact that homologous sequences share similar interactions, and, therefore, the set of interacting partners of the partners of a given protein is enriched by its homologs. The approach was bench-marked by assigning the fold and functional family to test sequences of known structure. Specifically, we relied on 1,434 proteins with known folds, as defined in the Structural Classification of Proteins (SCOP) database, and with known interacting partners, as defined in the Database of Interacting Proteins (DIP). For this subset, the specificity of fold assignment was increased from 54% for position-specific iterative BLAST to 75% for our approach, with a concomitant increase in sensitivity for a few percentage points. Similarly, the specificity of family assignment at the e-value threshold of 10(-8) was increased from 70% to 87%. The proposed method would be a useful tool for large-scale automated discovery of remote relationships between protein sequences, given its unique reliance on sequence similarity and protein-protein interactions.</style></abstract><notes><style face="normal" font="default" size="100%">Espadaler, Jordi Aragues, Ramon Eswar, Narayanan Marti-Renom, Marc A Querol, Enrique Aviles, Francesc X Sali, Andrej Oliva, Baldomero R01 GM54762/GM/NIGMS NIH HHS/United States Comparative Study Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov’t Research Support, U.S. Gov’t, P.H.S. United States Proceedings of the National Academy of Sciences of the United States of America Proc Natl Acad Sci U S A. 2005 May 17;102(20):7151-6. Epub 2005 May 9.</style></notes></record></records></xml>