Assessing predictions of protein–protein interaction: The CAPRI experiment

By Joël Janin. 2005

178 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

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Citations in the corpus

Pushing the limits of what is achievable in protein–DNA docking: benchmarking HADDOCK’s performance (2010, methodology): “The ability of HADDOCK to sample conformational space in search of the correct interaction interface(s) using ideal AIR restraints was evaluated using the CAPRI star ranking as a quality measure commonly used in protein–protein docking (31).”
SWISS-MODEL: homology modelling of protein structures and complexes (2018, neutral): “According to the community-wide experiment CAPRI (Critical Assessment of PRedicted Interactions (12)), considerable progress has been made in the field with the development of hybrid modelling strategies, that are able to incorporate available experimental information on the interaction (i.e.…”
The HADDOCK web server for data-driven biomolecular docking (2010, background): “CAPRI has proven to act as an important catalyst in the development of biomolecular docking approaches, with the result that accurate predictions for complexes that were considered beyond the limits of docking methodology a few years ago can nowadays be obtained 3,4 .”
Probing Native Protein Structures by Chemical Cross-linking, Mass Spectrometry, and Bioinformatics (2010, background): “Under such circumstances, up-to-date rigid body docking software is able to predict the correct topology with high probability (51, 52).”
Recent progress and future directions in protein-protein docking. (2008, unknown): “1389-2037/08 $55.00+.00 © 2008 Bentham Science Publishers Ltd. Keywords: Protein-protein docking, protein-protein interactions, docking algorithms, data-driven docking, molecular dynamics, protein structure databases, protein interface prediction, CAPRI.”
Prediction‐based fingerprints of protein–protein interactions (2006, background): “65 As before, only predictions for protein chains without sequence homology to any of the proteins used either for the training of SABLE or SPPIDER are included.”
Protein–protein interaction and quaternary structure (2008, methodology): “Since 2001, protein–protein docking is assessed by blind predictions in the CAPRI experiment (Critical Assessment of PRedicted Interactions ; Janin et al. 2003 ; Janin, 2005 ; Janin &Wodak, 2007).”
Information-Driven, Ensemble Flexible Peptide Docking Using HADDOCK. (2017, methodology): “…the performance of the docking, the interface RMSD measure from the community-wide experiment CAPRI (Critical Assessment of PRedicted Interactions) [31, 32] is used as criteria, which is calculated on interface residues by superimposing the docking solutions to the crystal structure of bound…”
The scoring of poses in protein-protein docking: current capabilities and future directions (2013, methodology): “These were used to classify the solutions as incorrect (f nat < 0.1 or (LRMSD > 10 Å and IRMSD > 4 Å)), acceptable ((f nat ≥ 0.3 and LRMSD > 5 Å and IRMSD > 2 Å) or ((f nat ≥ 0.1 and f nat < 0.3) and (LRMSD ≤ 10 Å or IRMSD ≤ 4 Å))), medium quality ((f nat ≥ 0.5 and LRMSD > 1 Å and IRMSD > 1 Å) or ((”
Accurate structure prediction of CDR H3 loops enabled by a novel structure-based C-terminal constraint (2016, background): “For a model to be considered a high-quality prediction by critical assessment of predicted interactions (CAPRI) metrics (45), the fraction of native residue–residue contacts recovered (fnat) must be $0.”
The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes. (2016, methodology): “The potential of data-driven docking is reflected in the success of the HADDOCK server and software in recent CAPRI experiments (Critical Assessment of Protein Interaction) [14,15], as well as in the number of structures deposited (>120) in the Protein Data Bank (PDB), which were calculated using ou”
MARTINI-Based Protein-DNA Coarse-Grained HADDOCKing (2019, methodology): “We evaluated the quality of the generated models following the standard CAPRI criteria (Janin, 2005).”