A protein‐RNA docking benchmark (II): Extended set from experimental and homology modeling data

@article{PerezCano2012APD,
  title={A protein‐RNA docking benchmark (II): Extended set from experimental and homology modeling data},
  author={L. Perez-Cano and B. Jim{\'e}nez-Garc{\'i}a and J. Fern{\'a}ndez-Recio},
  journal={Proteins: Structure},
  year={2012},
  volume={80}
}
We present here an extended protein–RNA docking benchmark composed of 71 test cases in which the coordinates of the interacting protein and RNA molecules are available from experimental structures, plus an additional set of 35 cases in which at least one of the interacting subunits is modeled by homology. All cases in the experimental set have available unbound protein structure, and include five cases with available unbound RNA structure, four cases with a pseudo‐unbound RNA structure, and 62… Expand
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References

SHOWING 1-10 OF 35 REFERENCES
Structural Prediction of Protein-RNA Interaction by Computational Docking with Propensity-Based Statistical Potentials
TLDR
This new protein-RNA docking protocol permits a fast scoring of rigid-body docking poses in order to select a small number of docking orientations, which can be later evaluated with more sophisticated energy-based scoring functions. Expand
Protein–protein docking benchmark version 4.0
TLDR
The protein–protein docking benchmark is updated to include complexes that became available since the previous release, and provides 176 unbound–unbound cases that can be used for protein– protein docking method development and assessment. Expand
Docking and scoring protein interactions: CAPRI 2009
TLDR
The ability of these algorithms to sample docking poses and to single out specific association modes in 14 targets, representing 11 distinct protein complexes, was evaluated, revealing that 67% of the groups, more than ever before, produced acceptable models or better for at least one target. Expand
Present and future challenges and limitations in protein–protein docking
TLDR
The limitations of the docking and energy‐based scoring approach are studied, and different parameters are analyzed to overcome the limitations and improve the docking performance. Expand
DARS-RNP and QUASI-RNP: New statistical potentials for protein-RNA docking
TLDR
Two medium-resolution, knowledge-based potentials for scoring protein-RNA models obtained by docking, including DARS-RNP, which showed the highest ability to identify native-like structures in both bound and unbound docking tests. Expand
Protein-protein docking tested in blind predictions: the CAPRI experiment.
  • J. Janin
  • Computer Science, Medicine
  • Molecular bioSystems
  • 2010
Docking algorithms build multimolecular assemblies based on the subunit structures. "Unbound" docking, which starts with the free molecules and allows for conformation changes, may be used to predictExpand
Optimal protein‐RNA area, OPRA: A propensity‐based method to identify RNA‐binding sites on proteins
Protein‐RNA interactions are essential in living organisms and they are involved in very different and important cellular processes. Thus, understanding protein‐RNA recognition at molecular level isExpand
A knowledge‐based potential function predicts the specificity and relative binding energy of RNA‐binding proteins
TLDR
This work demonstrates that statistical models allow the quantitative analysis of protein–RNA recognition based on their structure and can be applied to modeling protein– RNA interfaces for prediction and design purposes. Expand
A protein–DNA docking benchmark
TLDR
A protein–DNA docking benchmark containing 47 unbound–unbound test cases of which 13 are classified as easy, 22 as intermediate and 12 as difficult cases, a useful tool for comparison and development of protein– DNA docking methods. Expand
Dissection and prediction of RNA-binding sites on proteins
TLDR
A variety of computational methods for prediction of RNA-binding sites have been developed based either on protein sequence or on protein structure, and these methods will undoubtedly contribute to the identification and comprehension of protein-RNA interactions. Expand
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