QUEEN

QUEEN evaluates the informational content of experimental Nuclear Magnetic Resonance (NMR) restraints to quantify structural information relevant to biomolecular structure determination.

Key Features:

• Quantitative Information Assessment: Evaluates the informational content of experimental NMR restraints and provides measures that correlate with positional uncertainty of the NMR ensemble.
• Redundancy-Insensitive Measurement: Uses an information metric that is not influenced by redundancy within experimental restraints to represent unique structural information.
• Identification of Crucial Restraints: Identifies restraints that are significant and unique for structure determination to highlight the most informative data points.
• Enhanced Redundancy Detection: Detects a broader range of redundancies within experimental datasets compared to existing methods to refine datasets for structural analysis.

Scientific Applications:

• NMR-based Structure Determination: Quantifies restraint information to support biomolecular structure determination from NMR data.
• NOE and Restraint Evaluation: Provides quantitative evaluation of NOE data and other experimental restraints to assess their contribution to structural models.
• Experimental Design Optimization: Highlights which restraints most significantly reduce positional uncertainty to guide optimization of NMR experiments.

Methodology:

QUEEN combines distance-space descriptions with information-theory concepts to objectively quantify the informational content of experimental NMR restraints independent of redundancy effects.