ArticleProtein science : a publication of the Protein Society2006
An algorithm for predicting protein-protein interaction sites: Abnormally exposed amino acid residues and secondary structure elements.
Article in Protein science : a publication of the Protein Society, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Multi-task learning to leverage partially annotated data for PPI interface prediction.Scientific reports · 2022Article
- Protein-protein interaction prediction with deep learning: A comprehensive review.Computational and structural biotechnology journal · 2022Review
- Prediction of Protein-Protein Interaction Sites by Multifeature Fusion and RF with mRMR and IFS.Disease markers · 2022Article
- New feature extraction from phylogenetic profiles improved the performance of pathogen-host interactions.Frontiers in cellular and infection microbiology · 2022Article
- Classification and prediction of protein-protein interaction interface using machine learning algorithm.Scientific reports · 2021Article
- Deep Learning for Protein-Protein Interaction Site Prediction.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Article
- Accurate prediction of protein relative solvent accessibility using a balanced model.BioData mining · 2017Article
- Algorithmic approaches to protein-protein interaction site prediction.Algorithms for molecular biology : AMB · 2015Article
- Evolution of the Plant Reproduction Master Regulators LFY and the MADS Transcription Factors: The Role of Protein Structure in the Evolutionary Development of the Flower.Frontiers in plant science · 2015Article
- CRF-based models of protein surfaces improve protein-protein interaction site predictions.BMC bioinformatics · 2014Article
- Novel roles for α-crystallins in retinal function and disease.Progress in retinal and eye research · 2012Review
- Prediction of protein-protein interaction sites by random forest algorithm with mRMR and IFS.PloS one · 2012Article
- Computational design of a symmetric homodimer using β-strand assembly.Proceedings of the National Academy of Sciences of the United States of America · 2011Article
- Exploring weak, transient protein--protein interactions in crowded in vivo environments by in-cell nuclear magnetic resonance spectroscopy.Biochemistry · 2011Article
- Deciphering the shape and deformation of secondary structures through local conformation analysis.BMC structural biology · 2011Article
- Simplified method to predict mutual interactions of human transcription factors based on their primary structure.PloS one · 2011Article
- Article
- Using support vector machine combined with post-processing procedure to improve prediction of interface residues in transient complexes.The protein journal · 2009Article
- Amyloidogenic regions and interaction surfaces overlap in globular proteins related to conformational diseases.PLoS computational biology · 2009Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Multiprotein systems mediate most regulatory processes in living organisms. Although the structures of the individual proteins are often defined, less is known of the structures of multiprotein systems. Computational methods for predicting interfaces, using evolutionary conservation and/or physicochemical data, have been developed. Here we consider the use of solvent accessibility, residue propensity, and hydrophobicity, in conjunction with secondary structure data, as prediction parameters. We analyze the influence of residue type and secondary structure on solvent accessibility and define a measure of "relative exposedness." Clustering abnormally high scoring residues provides a basis for predicting interaction sites. The analysis is extended to investigate abnormally exposed secondary structure elements, particularly beta-sheet strands. We show that surface-exposed beta-strands lacking protective features are more likely to be found at protein-protein interfaces, allowing us to create an algorithm with approximately 68% and approximately 75% accuracy in differentiating between interacting and edge strands in isolated beta-strands and beta-sheet strands, respectively. These methods of identifying abnormally exposed surface regions are combined in an algorithm, which, on a data set of 77 unbound and disjoint (single chain extracted from complex) structures, predicts 79% of the protein-protein interfaces correctly. If enzyme-inhibitor complexes, where the inhibitor mimics a nonprotein substrate, are excluded, the accuracy increases to 85%.
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