Confidence Analysis of DEER Data and Its Structural Interpretation with Ensemble-Biased Metadynamics

Area of Science:

• Biophysics
• Structural Biology
• Spectroscopy

Background:

• Double electron-electron resonance (DEER) spectroscopy is crucial for determining biomolecular structural dynamics by measuring distances between spin probes.
• Current methods for assessing statistical errors in DEER-derived distance distributions are often non-standard, limiting rigorous interpretation.
• Tikhonov regularization, a common method for analyzing DEER data, poses challenges for accurate error estimation.

Purpose of the Study:

• To develop a robust methodology for calculating statistical errors in distance distributions obtained from DEER experiments.
• To provide confidence bands for DEER-derived distance probability distributions, enhancing structural interpretation.
• To generalize ensemble-biased metadynamics (EBMetaD) to incorporate uncertainty from DEER data.

Main Methods:

• A model-based approach representing distance probability distributions as sums of Gaussian components.
• Application of error propagation to calculate confidence bands, accounting for experimental noise, background signal uncertainty, and data collection time span.
• Generalization of ensemble-biased metadynamics (EBMetaD) to integrate confidence band information from DEER data.

Main Results:

• A novel method for generating confidence bands for DEER distance distributions, highlighting reliable and unreliable features.
• Demonstration that the generalized EBMetaD method accurately incorporates uncertainty from DEER measurements.
• Successful application and validation of the proposed techniques using DEER data from spin-labeled T4 lysozyme.

Conclusions:

• The developed error estimation method provides a rigorous framework for interpreting DEER-based structural dynamics.
• The generalized EBMetaD method enhances the accuracy of molecular simulations by accounting for DEER data uncertainty.
• These advancements offer improved tools for structural biologists utilizing DEER spectroscopy.