ArticleBMC bioinformatics2007
High-throughput identification of interacting protein-protein binding sites.
Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Prediction of Protein-Protein Interaction Sites Based on Stratified Attentional Mechanisms.Frontiers in genetics · 2021Article
- DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.Proteins · 2014Article
- Predicting protein-protein interface residues using local surface structural similarity.BMC bioinformatics · 2012Article
- Ranking Docked Models of Protein-Protein Complexes Using Predicted Partner-Specific Protein-Protein Interfaces: A Preliminary Study.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2011Article
- Prediction of protein binding sites in protein structures using hidden Markov support vector machine.BMC bioinformatics · 2009Article
- Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels.BMC bioinformatics · 2009Article
- Bridging protein local structures and protein functions.Amino acids · 2008Review
- Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundWith the advent of increasing sequence and structural data, a number of methods have been proposed to locate putative protein binding sites from protein surfaces. Therefore, methods that are able to identify whether these binding sites interact are needed.
resultsWe have developed a new method using a machine learning approach to detect if protein binding sites, once identified, interact with each other. The method exploits information relating to sequence and structural complementary across protein interfaces and has been tested on a non-redundant data set consisting of 584 homo-dimers and 198 hetero-dimers extracted from the PDB. Results indicate 87.4% of the interacting binding sites and 68.6% non-interacting binding sites were correctly identified. Furthermore, we built a pipeline that links this method to a modified version of our previously developed method that predicts the location of binding sites.
conclusionWe have demonstrated that this high-throughput pipeline is capable of identifying binding sites for proteins, their interacting binding sites and, ultimately, their binding partners on a large scale.
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Registered trials
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