ArticleBMC bioinformatics2011
Binding site prediction for protein-protein interactions and novel motif discovery using re-occurring polypeptide sequences.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Review
- Review
- PITHIA: Protein Interaction Site Prediction Using Multiple Sequence Alignments and Attention.International journal of molecular sciences · 2022Article
- Evaluation of the Effectiveness of Derived Features of AlphaFold2 on Single-Sequence Protein Binding Site Prediction.Biology · 2022Article
- Multi-schema computational prediction of the comprehensive SARS-CoV-2 vs. human interactome.PeerJ · 2021Article
- Pattern to Knowledge: Deep Knowledge-Directed Machine Learning for Residue-Residue Interaction Prediction.Scientific reports · 2018Article
- Reciprocal Perspective for Improved Protein-Protein Interaction Prediction.Scientific reports · 2018Article
- Conversion of Protein Active Regions into Peptidomimetic Therapeutic Leads Using Backbone Cyclization and Cycloscan - How to Do it Yourself!Current topics in medicinal chemistry · 2018Review
- Progress and challenges in predicting protein interfaces.Briefings in bioinformatics · 2016Review
- Article
- SPPS: a sequence-based method for predicting probability of protein-protein interaction partners.PloS one · 2012Article
- Partner-aware prediction of interacting residues in protein-protein complexes from sequence data.PloS one · 2011Article
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundWhile there are many methods for predicting protein-protein interaction, very few can determine the specific site of interaction on each protein. Characterization of the specific sequence regions mediating interaction (binding sites) is crucial for an understanding of cellular pathways. Experimental methods often report false binding sites due to experimental limitations, while computational methods tend to require data which is not available at the proteome-scale. Here we present PIPE-Sites, a novel method of protein specific binding site prediction based on pairs of re-occurring polypeptide sequences, which have been previously shown to accurately predict protein-protein interactions. PIPE-Sites operates at high specificity and requires only the sequences of query proteins and a database of known binary interactions with no binding site data, making it applicable to binding site prediction at the proteome-scale.
resultsPIPE-Sites was evaluated using a dataset of 265 yeast and 423 human interacting proteins pairs with experimentally-determined binding sites. We found that PIPE-Sites predictions were closer to the confirmed binding site than those of two existing binding site prediction methods based on domain-domain interactions, when applied to the same dataset. Finally, we applied PIPE-Sites to two datasets of 2347 yeast and 14,438 human novel interacting protein pairs predicted to interact with high confidence. An analysis of the predicted interaction sites revealed a number of protein subsequences which are highly re-occurring in binding sites and which may represent novel binding motifs.
conclusionsPIPE-Sites is an accurate method for predicting protein binding sites and is applicable to the proteome-scale. Thus, PIPE-Sites could be useful for exhaustive analysis of protein binding patterns in whole proteomes as well as discovery of novel binding motifs. PIPE-Sites is available online at http://pipe-sites.cgmlab.org/.
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