02280nas a2200169   4500008004100000245007900041210006900120520169500189653002001884100001501904700001601919700001801935700002401953700001301977700001401990856010602004       2009                        eng d00aModLink+: Improving fold recognition by using protein-protein interactions0 aModLink Improving fold recognition by using proteinprotein inter3 a<p>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.</p>10aprotein folding1 aFornes, O.1 aAragues, R.1 aEspadaler, J.1 aMarti-Renom, M., A.1 aSali, A.1 aOliva, B.  uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1935710002608nas a2200217   4500008004100000245009500041210006900136300001200205490000600217520172500223653008401948653002102032653012902053653002102182100001602203700001302219700001402232700002402246700001402270856010602284       2007                        eng d00aCharacterization of protein hubs by inferring interacting motifs from protein interactions0 aCharacterization of protein hubs by inferring interacting motifs  a1761-710 v33 aThe characterization of protein interactions is essential for understanding biological systems. While genome-scale methods are available for identifying interacting proteins, they do not pinpoint the interacting motifs (e.g., a domain, sequence segments, a binding site, or a set of residues). Here, we develop and apply a method for delineating the interacting motifs of hub proteins (i.e., highly connected proteins). The method relies on the observation that proteins with common interaction partners tend to interact with these partners through a common interacting motif. The sole input for the method are binary protein interactions; neither sequence nor structure information is needed. The approach is evaluated by comparing the inferred interacting motifs with domain families defined for 368 proteins in the Structural Classification of Proteins (SCOP). The positive predictive value of the method for detecting proteins with common SCOP families is 75% at sensitivity of 10%. Most of the inferred interacting motifs were significantly associated with sequence patterns, which could be responsible for the common interactions. We find that yeast hubs with multiple interacting motifs are more likely to be essential than hubs with one or two interacting motifs, thus rationalizing the previously observed correlation between essentiality and the number of interacting partners of a protein. We also find that yeast hubs with multiple interacting motifs evolve slower than the average protein, contrary to the hubs with one or two interacting motifs. The proposed method will help us discover unknown interacting motifs and provide biological insights about protein hubs and their roles in interaction networks.10aAmino Acid Motifs Amino Acid Sequence Binding Sites Computer Simulation *Models10aChemical *Models10aMolecular Molecular Sequence Data Protein Binding Protein Interaction Mapping/*methods Proteins/*chemistry Sequence Analysis10aProtein/*methods1 aAragues, R.1 aSali, A.1 aBonet, J.1 aMarti-Renom, M., A.1 aOliva, B.  uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1794170502245nas a2200253   4500008004100000245008600041210006900127300001100196490000800207520134200215653001501557653003601572653012101608653002301729100001801752700001601770700001401786700002401800700001501824700001901839700001301858700001401871856010601885       2005                        eng d00aDetecting remotely related proteins by their interactions and sequence similarity0 aDetecting remotely related proteins by their interactions and se  a7151-60 v1023 aThe 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.10aAmino Acid10aComputational Biology Databases10aMolecular Protein Conformation Protein Folding Proteins/*genetics/*metabolism Proteomics/*methods *Sequence Homology10aProtein *Evolution1 aEspadaler, J.1 aAragues, R.1 aEswar, N.1 aMarti-Renom, M., A.1 aQuerol, E.1 aAviles, F., X.1 aSali, A.1 aOliva, B.  uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15883372