Integrating Electron Paramagnetic Resonance Spectroscopy and Computational Modeling to Measure Protein Structure and Dynamics

Abstract

Electron paramagnetic resonance (EPR) has become a powerful probe of conformational heterogeneity and dynamics of biomolecules. In this review, we discuss different computational modeling techniques that enrich the interpretation of EPR measurements of dynamics or distance restraints. A variety of spin labels are surveyed to provide a background for the discussion of modeling tools. Molecular dynamics (MD) simulations of models containing spin labels provide dynamical properties of biomolecules and their labels. These simulations can be used to predict EPR spectra, sample stable conformations and sample rotameric preferences of label sidechains. For molecular motions longer than milliseconds, enhanced sampling strategies and de novo prediction software incorporating or validated by EPR measurements are able to efficiently refine or predict protein conformations, respectively. To sample large‐amplitude conformational transition, a coarse‐grained or an atomistic weighted ensemble (WE) strategy can be guided with EPR insights. Looking forward, we anticipate an integrative strategy for efficient sampling of alternate conformations by de novo predictions, followed by validations by systematic EPR measurements and MD simulations. Continuous pathways between alternate states can be further sampled by WE‐MD including all intermediate states.

Modeling of Cu(ii)-based protein spin labels using rotamer libraries

“…Protein backbone diversity can be generated using elastic network modeling, as implemented in MMM and MMMx 38,86 or using MD simulations, especially with the use of enhanced sampling methods. 72,87,88 As a scriptable Python-based API, chiLife can easily be integrated with an implementation of the same, or an equivalent elastic network modelling protocol, utilize full MD trajectories of native proteins as inputs to model Cu–Cu distance distributions, or integrate with other modelling software like Rosetta 17,89 and Xplor-NIH, 90 allowing dHis-Cu( ii )-NTA distance constraints to be used in a wide variety of existing and future analysis and protein modelling pipelines.…”

Currently Used Methods to Evaluate the Efficacy of Therapeutic Drugs and Kidney Safety

“…Importantly, these simulations can also forecast how biomolecules react to alterations like mutations, phosphorylation, protonation, or the addition or removal of ligands at the atomic level. A wide range of experimental structural biology techniques, such as x-ray crystallography [120], cryo-electron microscopy (cryo-EM) [121], nuclear magnetic resonance (NMR) [122], electron paramagnetic resonance (EPR) [123], and fluorescence resonance energy transfer (FRET) [124] are frequently utilized in conjunction with MD simulations. To study the treatments for kidney failure, MD simulations can applied to investigate several innovative drugs for treating kidney diseases.…”