ArticleProtein science : a publication of the Protein Society2011
On the analysis of protein-protein interactions via knowledge-based potentials for the prediction of protein-protein docking.
Article in Protein science : a publication of the Protein Society, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
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- The Molecular Docking of MAX Fungal Effectors with Plant HMA Domain-Binding Proteins.International journal of molecular sciences · 2023Article
- Modeling Protein Complexes and Molecular Assemblies Using Computational Methods.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Prediction of Protein-Protein Binding Affinities from Unbound Protein Structures.Methods in molecular biology (Clifton, N.J.) · 2022Review
- Classification and prediction of protein-protein interaction interface using machine learning algorithm.Scientific reports · 2021Article
- SPServer: split-statistical potentials for the analysis of protein structures and protein-protein interactions.BMC bioinformatics · 2021Article
- Using collections of structural models to predict changes of binding affinity caused by mutations in protein-protein interactions.Protein science : a publication of the Protein Society · 2020Article
- On the prediction of DNA-binding preferences of C2H2-ZF domains using structural models: application on human CTCF.NAR genomics and bioinformatics · 2020Article
- Evaluation of CONSRANK-Like Scoring Functions for Rescoring Ensembles of Protein-Protein Docking Poses.Frontiers in molecular biosciences · 2020Article
- Wnt Binding Affinity Prediction for Putative Frizzled-Type Cysteine-Rich Domains.International journal of molecular sciences · 2019Article
- On the mechanisms of protein interactions: predicting their affinity from unbound tertiary structures.Bioinformatics (Oxford, England) · 2018Article
- Protein-protein interaction specificity is captured by contact preferences and interface composition.Bioinformatics (Oxford, England) · 2018Article
- A machine learning approach for ranking clusters of docked protein-protein complexes by pairwise cluster comparison.Proteins · 2017Article
- Article
- The scoring of poses in protein-protein docking: current capabilities and future directions.BMC bioinformatics · 2013Article
- Fast and accurate modeling of protein-protein interactions by combining template-interface-based docking with flexible refinement.Proteins · 2012Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions for selecting rigid-body docking poses. These potentials include the energetic component that provides the residues with a particular secondary structure and surface accessibility. These scoring functions have been tested on a state-of-art benchmark dataset and on a decoy dataset of permanent interactions. Our results were compared with a residue-pair potential scoring function (RPScore) and an atomic-detailed scoring function (Zrank). We have combined knowledge-based potentials to score protein-protein poses of decoys of complexes classified either as transient or as permanent protein-protein interactions. Being defined from residue-pair statistical potentials and not requiring of an atomic level description, our method surpassed Zrank for scoring rigid-docking decoys where the unbound partners of an interaction have to endure conformational changes upon binding. However, when only moderate conformational changes are required (in rigid docking) or when the right conformational changes are ensured (in flexible docking), Zrank is the most successful scoring function. Finally, our study suggests that the physicochemical properties necessary for the binding are allocated on the proteins previous to its binding and with independence of the partner. This information is encoded at the residue level and could be easily incorporated in the initial grid scoring for Fast Fourier Transform rigid-body docking methods.
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